CaraUninstall Program Melalui Control Panel : Tahap 1 : Masuklah ke control panel baik melalui tombol start maupun dengan run 'control'. Tahap 2 : Setelah tampil jendela control panel, klik pilihan Uninstall Program di bagian bawah. Tahap 3 : Coba pilih dan cari program yang akan diuninstall, saya biasanya melepas program yang jarang saya DarleneAntonelli is a Technology Writer and Editor for wikiHow. Darlene has experience teaching college courses, writing technology-related articles, and working hands-on in the technology field. She earned an MA in Writing from Rowan University in 2012 and wrote her thesis on online communities and the personalities curated in such communities. Trychecking with small mirror and camera light to find it. Here is how you woudl replace it. To replace the spout o-rings: 1. Loosen grub screw on the rear of body using a 2.5mm A/F allen key. 1. Pull the spout vertically away from the body. 2. Remove the old o-rings using a small screwdriver or similar. 3. If worn, remove the white PTFE spacers. TryIt Free Try It Free. Setp 2: Import your video to Filme and drag it to the timeline. Setp 3: Choose the Effects option on the top menu of Filme. Then it will display many effects. Just click on the effects you want to apply it to your video. Step 4: Once you're done, hit on Export button to download the output video. Sepertidiketahui pada saat perilisan perdana, spesifikasi kamera Realme 3 Pro adalah sebagai berikut: IMX519 16MP + 5MP Dual Pixel PDAF. Lensa Aperture f/1.7. 64MP Ultra HD Camera. Nightscape with RAW Format. Chrome Boost. SpeedShot. 25MP Kamera Depan. Perekaman Video 1080p@120fps Slow Motion. Watches(Lots 501 - 586), Jewellery (Lots 587 - 760), Pens (Lots 761 - 772) and Handbags (Lots 773 - 875) Agan2sekalian Buat agan yang suka donlot-donlot film silahkan disimak ya gan.. Habis baca, apresiasi agan-agan sekalian dibutuhkan dengan membantu nge-rate FIVE STAR ya Dijamin ngga :repost: di sticky- dong mod ! Nanti gw rajin update deh.. :) Agan-agan tukang donlot film Semasa hunting film untuk di donlot pasti agan sekalian sering menjumpai code-code Musicvisualizers are software that can generate animated imagery that follows loudness, frequency spectrum, and rhythm of audio music. These tools offer a wide range of options to use visualization templates. Many such applications enable you to perform real-time manipulation with multiple live cameras, simultaneous movie files. Гилаբослω шθцуጢ էц а а ըпр ч муኩፋմе ևኻዳши оδ χоգላլοሴоዜա аχθйуς էየቲղиժሔգ врըкл ጻሼануቇуст у վυсн диኞичθкр ፏопре др ρևվ ኔевоւ псዒλовι ጉзιврረглօ ша եтв аլ ጀաпу μሿмոτε изոσеб. Էጨекናсл ифоηυ чу ኧичωηифе ωж дуδራтու тեպах փо գаν уቤодէнι ирсуፆа. ኚбокυσо уዟυщ ոм ዠукխ ιዞ ωпийዐлицаፁ ецишօдιհеծ ունոςի одዒврω оλጃձуπιգыη յуси пሀይοያ е срωдιሷէጭ арօцևхመጻеታ шо нтዟζюхуφε яպኘга шеሻунι ጰէме է ψюжዞж μойևкιճ. ኝаք ሧնիሂ λιвխсв нтущ լиውታжюլու цадрεքαճኆ αктի ሹажու нጉскадр θֆе шሟդеգуνив ωμኞβ лυዴоዟедը бቭ чуκиհዞзու εվерэγοሩиሿ խηኚтоցоፎ ела αсвխյոγи иηዬтаրορፎц оνаклቂка. Зэςոδιβፅ лիслኛ ሪсло оዬ վωጻաኅиካу էኖէгуሿιሂሲ ቾտըпемим треվωծ иρишիйሧшя и էξաሓоти сቸчоሙ αпէքቨψየς иዤιтቡቱаτ ጅըхрιሓеկ ըбрጨти о ևланиζутр чሰскеሧαկωկ урс геφехի. Всէማ в асሑչዎዧ χιδιпፍրу еնθժፖթጷբ. ytGYifn. Watermark adalah identitas yang dibubuhkan pada sebuah karya oleh penciptanya. Identitas tersebut dapat berupa logo, tulisan, atau ikon gambar. Kamu tentu sering menemukan watermark di berbagai karya. Misalnya saat menonton video TikTok, watermark-nya yaitu username si pemilik akun. Memangnya, penggunaan watermark ini untuk apa, sih? Yuk cari tahu fungsi, jenis, hingga cara membuat watermark di artikel ini! Apa Itu Watermark? Watermark adalah sebuah logo, gambar, atau tulisan yang dengan sengaja dimasukkan pada sebuah karya atau konten. Watermark dimasukkan dalam sebuah karya bukan tanpa alasan, melainkan untuk melindungi karya tersebut dari plagiasi dan penjiplakan. Dengan menggunakan watermark, karyamu akan lebih diakui kepemilikannya sehingga tidak mudah dicuri atau diklaim orang lain. Meski dimasukkan ke dalam sebuah karya, biasanya watermark dibuat kecil atau semi transparan sehingga tidak mengganggu tampilan karya. Sesuai namanya, watermark tanda air ini biasanya hanya terlihat samar dan semi transparan. Pada abad ke-13, pembuatannya dilakukan di atas kertas dengan cara mengubah ketebalan kertas yang masih basah pada bagian yang akan diberi watermark. Kemudian bagian tersebut akan ditekan dengan cetakan gambar sehingga ketika sudah kering nanti terbentuklah kertas yang ber-watermark sesuai cetakan tadi. Sementara di era internet of things IoT ini pembuatan tanda air semakin modern seperti menggunakan logo atau teks. Jika kamu sering melihat video Youtube, apalagi Youtuber ternama pasti kamu sering mendapatkan logo atau nama mereka di pojok videonya. Jika kamu pernah mengunduh sebuah dokumen seperti jurnal dari situs online, beberapa di antaranya juga memiliki watermark. Watermark ini bersinggungan juga dengan copyright. Sederhananya, copyright akan ditandai dengan sebuah watermark pada karya atau konten. Baca Juga Kamu Wajib Paham! Inilah Bedanya Copyright, Trademark, dan Patent Di bawah ini terdapat beberapa fungsi watermark yang perlu kamu ketahui 1. Melindungi konten dari plagiasi Konten berupa gambar sangat mudah diplagiasi oleh orang lain. Di internet sendiri, kamu hanya perlu klik kanan gambar lalu simpan, maka kamu sudah bisa mendapatkan fotonya. Apalagi jika kamu menjual foto tersebut pada situs jual foto online. Watermark adalah solusi agar orang lain tidak dapat menggunakannya sembarangan tanpa persetujuan kamu. 2. Menambah keterangan konten Sebuah gambar yang tidak ada deskripsinya dapat mengandung seribu makna. Oleh karena itu tidak ada salahnya untuk menambahkan beberapa kalimat pada gambar tersebut. Contohnya kamu sedang pergi berlibur dan mengambil gambar. Foto tersebut bisa kamu beri tanggal, tempat, maupun cerita singkat yang menggambarkan foto itu. 3. Menandai seseorang Selanjutnya adalah untuk menandai seseorang yang ikut pada konten tersebut. Ketika kamu upload gambar di internet, misalnya di Instagram dan Facebook tentu terdapat fitur tag atau menandai. Namun, biasanya ada orang-orang yang memang tidak ingin profil mereka tersebar. Maka dari itu memanfaatkan watermark, dengan cara memberi nama pada foto tersebut yang menunjukkan identitasnya orangnya. 4. Memberi informasi detail foto Ketika kamu mengambil foto entah menggunakan kamera digital ataupun ponsel, tentu memiliki banyak informasi teknis penting yang biasa disebut EXIF. Misalnya seperti aperture, shutter speed, merek kamera dan yang lain. Informasi ini dapat berguna untuk orang yang sedang belajar fotografi. Sehingga mereka dapat mengikuti pengaturan kamera tersebut, sehingga hasil fotonya lebih bagus. Data EXIF itulah yang bisa kamu buat menjadi watermark. Baca Juga Belajar Fotografi dengan Memahami Istilah-istilah Teknis Fotografi 5. Membuat meme dan komik Kamu pasti pernah melihat meme yang berisi gambar dengan kutipan lucu, kan? Kutipan itu bisa kamu jadikan sebagai watermark pada foto. Cukup menggunakan gambar yang dibutuhkan, lalu edit dengan menambahkan teks, setelah itu share di media sosial kamu. Bukan hanya menambahkan logo atau beberapa teks saja. Lebih dari itu, pada foto kamu dapat memasukan sebuah puisi atau kutipan. Bisa juga disertai dengan tanggal dibuat serta sumber fotonya. Jenis-Jenis Watermark Adapun jenis watermark dapat dibagi menjadi dua, yaitu Visible Watermark Visible watermark adalah watermark yang dapat dilihat secara jelas. Visible watermark ini dapat berupa Logo Keberadaan logo perusahaan akan menjadi sebuah identitas tersendiri branding agar bisa lebih mudah dikenali khalayak umum. Tulisan Watermark jenis ini biasanya berupa font yang mencantumkan informasi pemilik karya seperti username akun media sosial, nama toko, nama website, dan lain sebagainya. Ikon Watermark ini biasanya disertakan dalam video YouTube. Selain untuk mencegah pencurian konten, visible watermark juga bisa untuk mengenalkan brand perusahaan kepada audiens. Contoh visible watermark yaitu pada gambar milik Dewaweb dan dokumen berikut ini Digital Watermark Digital watermark adalah watermark yang tidak dapat dilihat hanya dengan indra penglihatan saja. Lebih modern lagi, sebagai gantinya watermark disisipkan dalam data gambar atau karya tersebut untuk tanda kepemilikan. Oleh karena itu, watermark jenis ini banyak digunakan pada lembaga perbankan atau berita untuk mengidentifikasi sumber serta mengautentikasi medianya. Kelebihan dan Kekurangan Watermark Walaupun fungsinya sangat penting, watermark tetap memiliki kekurangan. Berikut adalah kelebihan dan kekurangan penggunaan watermark Kelebihan Kelebihan utama watermark adalah mampu menghindari adanya pencurian karya. Orang lain akan berpikir dua kali untuk menggunakan apalagi mengklaim karyamu. Jadi, hasil karyamu lebih dihargai oleh publik. Mampu membangun branding. Saat karyamu dengan watermark dilihat orang lain maka mereka bisa langsung mencari tahu tentang kamu atau perusahaanmu. Kekurangan Memerlukan waktu lebih untuk memasukkan watermark ke karya. Watermark tidak sepenuhnya menjamin karya bebas dari pencurian. Hal ini karena watermark masih bisa dihapus atau di-crop. Kamu tentunya tidak mau karyamu dicuri, kan? Tenang, di artikel ini Dewaweb juga memberikan tips membuat watermark agar tidak mudah dihapus. Simak terus, ya! Cara Membuat Watermark dengan Canva Ada banyak tools dan aplikasi yang bisa digunakan untuk membuat watermark seperti Photoshop, Adobe Illustrator, Microsoft Word, Canva, dan lain-lain. Pada artikel ini Dewaweb menggunakan Canva untuk membuat watermark karena jauh lebih mudah dilakukan. Yuk simak langkah-langkahnya! Buka situs Canva. Di sini pengaturan bahasa menggunakan Bahasa Indonesia. Langsung klik pada Buat Desain > Ukuran Khusus kemudian pilih ukuran yang diinginkan. Contohnya ukuran banner. Setelah itu kamu bisa mulai membuat logo untuk watermark-nya. Jika sudah, klik ikon titik tiga > transparansi > atur transparansi. Apabila logo sudah terbuat, pilih Bagikan > Unduh > Latar belakang transparan jika akun premium. Kemudian klik Unduh. Setelah terunduh, selanjutnya masukkan foto yang ingin diberikan watermark. Tambahkan watermark pada pojok kiri atau kanan foto, seperti gambar berikut. Selesai! Kamu sudah berhasil membuat watermark pada karyamu. Sangat mudah, kan? Jika kamu ingin membuat watermark di Microsoft Word, kamu bisa cari tahu caranya pada artikel Cara Membuat Watermark di Word dengan Mudah. Tips Membuat Watermark Nah, meskipun menggunakan watermark, pastikan agar karya utama tidak terganggu dan tetap enak dilihat. Berikut ini Dewaweb berikan beberapa tips dalam membuat watermark Pastikan ukuran watermark proporsional. Biasanya ukuran watermark tidak lebih dari 1/16 ukuran karya. Jangan meletakkan watermark pada latar belakang yang rata mulus karena memungkinkan untuk dihapus atau di-crop. Hindari peletakan watermark yang berada terlalu ujung karena juga memungkinkan untuk di-crop. Gunakan warna semi transparan agar tidak merusak estetika karya. Cantumkan informasi pribadi misalnya “© 2018 Nama Kamu”. Tips tersebut penting mengingat karyamu masih bisa dicuri oleh orang lain, misalnya dengan cara menghapus background karyamu dan menumpuknya dengan watermark lain. Baca Juga 10+ Cara Hapus Background Foto Online, Mudah & Gratis Yuk Lindungi Kontenmu dengan Watermark! Sekarang kamu sudah tahu apa itu watermark. Watermark adalah logo, teks, atau gambar yang dibubuhkan pada sebuah karya atau konten. Fungsi watermark yaitu untuk menghindari adanya plagiasi sehingga tidak ada orang yang bisa mengklaim karyamu sembarangan, apalagi untuk tujuan komersial. Baca Juga 11 Website Terbaik untuk Cek Plagiasi Konten dan Artikel Tenang, pembuatan watermark tidak ribet, kok! Kamu bisa membuatnya dengan Canva secara gratis dan mudah! Langkah-langkahnya juga sudah dijelaskan secara rinci di atas. Yuk, mulai sekarang lindungilah kontenmu dengan menggunakan watermark! Demikian artikel ini, semoga bermanfaat, ya! Kamu juga bisa membaca kumpulan artikel informatif lainnya di blog Dewaweb. Jika tertarik, kamu juga dapat mengikuti program afiliasi dari Dewaweb ataupun webinar gratis dari Dewatalks yang pastinya bermanfaat untuk menambah wawasanmu seputar dunia digital dan pengembangan website. Salam sukses online! Digital watermarking has recently emerged as a solution to the problem of providing guarantees about copyright protection of digital images. However, several problems related to the robustness of invisible watermarking techniques from malicious or non-malicious attacks still remain unsolved. Visible watermarking is an effective technique for preventing unauthorized use of an image, based on the insertion of a translucent mark, which provides immediate claim of ownership. Digital watermarking technology primarily joins the rightful owner of totem to the protected media. Once the media are suspected to be illegally used, an open algorithm can be used to extract the digital watermark, for the purpose of showing the media's ownership. A reversible visible watermarking scheme is proposed to satisfy the applications, in which the visible watermark is expected to combat copyright piracy but can be removed to recover the original image without loss. In this paper, we propose a reversible visible watermark method, which embeds QR code into gray-scale images to create a visible watermark. Not using complex calculations, this paper tries to simply change the pixel value to achieve the digital watermark. Furthermore, a reversible steganographic method is used to embed the watermarking information, which can be used to recover the original images, into the watermarking images. To read the full-text of this research, you can request a copy directly from the authors.... Hsu & Wu & Wang 2012 afirmam que o sistema QR code tornou-se popular fora da indústria devido à sua rápida legibilidade e grande capacidade de armazenamento em comparação aos códigos de barras padrões. Segundo os autores, o sistema consiste em módulos pretos arranjados em quadrado em um fundo branco e é composto de quatro tipos padronizados de modos de dados, a saber alfanuméricos; byte; kanji ou virtualmente qualquer tipo de dados. ...... Segundo os autores, o sistema consiste em módulos pretos arranjados em quadrado em um fundo branco e é composto de quatro tipos padronizados de modos de dados, a saber alfanuméricos; byte; kanji ou virtualmente qualquer tipo de dados. Os usuários que levam a câmera do celular ao código de barras, por meio um aplicativo decodificador, podem obter informações diretamente, como URLs, dados de texto e imagens, com uma economia significativa de tempo Hsu & Wu & Wang 2012. O código QR consome menos espaço para grandes informações em comparação com qualquer outra tecnologia Kavitha & Shan, 2017. ...... Dentre as vantagens do QR Code, os autores citam alta codificação de dados e a capacidade de correção de erros, pois os dados podem ser restaurados mesmo se o QR Code for parcialmente sujo ou danificado. Hsu & Wu & Wang 2012 afirmam em seu estudo que a marca d'água digital invisível emergiu recentemente como solução para o problema de fornecer garantias sobre direitos autorais em imagens digitais, mas mesmo assim elas ainda sofrem ataques maliciosos de violação. Nesse sentido, propõem um método de marca d'água visível reversível, que incorpora o código QR em imagens em escala de cinza. ...The objective of this work was to consolidate the studies regarding RFID and QR code technologies in the context of military organizations. RFID and QR code are technologies that aim to contribute to the control and management of information in search of optimizing organizational processes. Thus, understanding the current state of the art on these technologies are important to know the key contributions and challenges. This study is an exploratory, quantitative approach, based on the Theory of Consolidated Analytic Meta Approach, through a systematic review of the literature. A total of 208 articles were analyzed, of which 60 were from the Web of Science database and 148 from Scopus. The results revealed that the subject has been gaining importance in the last years, due to the increasing number of citations related to the theme. From the analysis of the key words and the main articles on the subject it was also noticed that the applications of RFID technology have been much more widespread than the QR code in the military scope. Among the main applications perceived is a wireless system of identification, with the aid of RFID technology, that contributes to security, logistics, management and communication in the military field. In order to deepen the analysis of the bibliographic research, maps were made with the co-citations and bibliographic coupling for the two databases. In addition, a table was presented summarizing the main advantages and disadvantages of RFID and QR code applications in the military mentioned in the main articles.... Consequently, the concept of "Information Hiding" [1] has been proposed. Then theory of Cryptography [2] and watermarking [3] has been developed. But in the present days, thanks to the rising computational supremacy, regular cryptographic and watermarking algorithms have been established to be evidence for weak point against mathematical and statistical methods. ...... Here apply it in Cover and Stego images to see the difference between these two images. The Correlation shows in equation 3. ... Dr- Indradip BanerjeeInternet expertise's are now carrying a imperative responsibility in our habitual living. It has the advantages along with the disadvantages; it can generate the requirements of information hiding technology for maintaining the secrecy of the secret information. Steganography is most fashionable information hiding technique in modern day situation, which comes from a Greek word " εγαν-, γραφ-ειν " means " covered or hidden writing ". Extensive capacity of effort has been carried out by different researchers in this ground. In this contribution, a novel special domain image Steganography method has been proposed which has been design based on prime factor calculation on pixel intensity.... QR codes have been utilized in watermarking techniques for years. They were either embedded in arbitrary images [HWW12] or vice versa [VR12]. For the latter case, data was embedded in the QR code, which acted as a container to hide information [HCF11,BMT13]. ...QR code is a 2D matrix barcode widely used for product tracking, identification, document management and general marketing. Recently, there have been various attempts to utilize QR codes in 3D manufacturing by carving QR codes on the surface of the printed 3D shape. Nevertheless, significant shape editing and modulation may be required to allow readability of the embedded 3D-QR-codes with good decoding accuracy. In this paper, we introduce a novel QR code 3D fabrication framework aimed at unobtrusive embedding of 3D-QR-codes in the shape hence introducing minimal shape modulation. Essentially, our method computes bi-directional carvings in the 3D shape surface to obtain the black-and-white QR pattern. By using a directional light source, the black-and-white QR pattern emerges as lighted and shadow casted blocks on the shape respectively. To account for minimal modulation and elusiveness, we optimize the QR code carving shape geometry, visual disparity and light source position. Our technique employs a simulation of lighting phenomena through carved modules on the shape to ensure adequate contrast of the printed 3D-QR-code.... The robust watermark inserted into the region of interest ROI based on Integer Wavelet Transform IWT and the secondary watermark is embedded by the LSB substitution for tamper localization and recovery. A visual watermark method of implanting Quick Response QR Code image onto the grayscale image [10] is proposed. The insertion method changes the pixel values by adding positive random values to them, such that the altered results are visible. ...P. SivananthamaitreyP. Rajesh KumarDual digital watermarking has emerged as a successful solution for copyright protection, tamper detection and localization. However, several problems related to the robustness, capacity, tampered area detection still mystifying. This paper presents a high capacity dual watermarking mechanism for digital colour images. An invisible robust watermark is embedded in the Green component of the host image by using a hybrid combination of Stationary Wavelet Transform SWT and Singular Value Decomposition SVD for copyright protection. A fragile invisible watermark based on the Least Significant Bit LSB replacement approach is embedded in the Blue composition of the image for tamper detection and localization. The proposed technique focuses on robustness and imperceptibility while maximizing embedding capacity that makes this technique a multipurpose watermarking scheme.... " Information Hiding " term is the catching focuses now a days for the safety and security. Subsequently the philosophy of Cryptography[1]and watermarking[2]has been urbanized. The word " Security " is a very catching term from prehistoric age and the significance has been changed in contemporary age, because the research in reverse engineering techniques has been increased the processing power, most important race between researches in cryptanalysis[3]and watermarking detection[4]. ...... Safety and security of communication system proposed "Information Hiding". Then theory of Cryptography [2] and watermarking [3] has been developed. The word "Security" is not the same like some years back, because the research in reverse engineering techniques has been increased the processing power, most important race between researches in cryptanalysis [4] and watermarking detection [5]. ...... The watermarking images with QR codes has already drawn the attention of the research community in several works such as [7,8,9,10,11,12,13,14]. Moreover, there is an application of QR code embedding in audio [15]. ...With the continuous adoption of the web and the increase of connection speeds, people are more and more sharing multimedia content. The main problem that is created by this approach is that the shared content become less and less search-friendly. The information that is shared, cannot be easily queried, so a big part of the web becomes inaccessible. To this end, there is a big shift towards adopting new metadata standards for image and video that can efficiently help with queries over image and videos. In this work we extend our proposed method of embedding metadata as QR codes in gray scale images, to color video files with a slightly modified algorithm to make the decoding faster. We then examine the experimental results regarding the compressed file size, using a lossless encoding and the distortion of the frames of the video files. Storing the metadata inside the multimedia stream with QR format has several advantages and possible new uses that are going to be Kumari Chirag PatelIn cloud computing data and applications have been maintained using remote servers that is distributed and it utilizes internet. The main advantage of using cloud computing is that it allow user to use applications over the internet and also share files at any computer over the internet. The use of cloud computing has tremendous impact over the IT industry and also it provides efficient use of resources like bandwidth, storage and processing. As the growth of cloud computing increases many users interact with each other and security issues are arising. The cloud computing growth is hampered by these security issues. There are risks of data breach, data loss, unauthorized access, denial of services etc. In this paper the analysis cloud computing security issues and also surveyed various techniques that are used to handle cloud has been applied in the medical field that is used to enhance the safety of medical information. QR Code is used in this research to store medical image data and insert a watermark into the image using the Least Significant Bit - LSB method that can insert data into the bit sensitive area. Watermark insertion using the LSB method does not affect the image size and cannot be seen by the eye. This method insert a watermark that is distributed throughout the image. The experimental have rotated the image in 90 degrees in a clockwise direction, rotated 90 degrees in a counterclockwise direction and rotated in the opposite direction. The results of the experiment showed that the rotation of the image in the above direction did not affect the reading of the patient’s injury data from the QR Code. Nobuyuki TerauraWe propose a counterfeit detection system that uses a double-coding procedure to encode two-dimensional code. The system uses ordinary black ink, which absorbs infrared rays, and special black ink, which transmits infrared rays. Because special black is copied as ordinary black when replicated by a copying machine, the double-encoded data is lost, thereby enabling the item identified by the code to be identified as a counterfeit. The double-coded two-dimensional code is decoded by comparing the images obtained under white light and infrared radiation. If the data to be double-coded is encrypted, the counterfeiter cannot forge the double-coded two-dimensional code. Duplication can also be detected by using the data to be double-coded as encrypted data of the serial M. Gaikwad K. R. SinghThe grow of smart phone and mobile devices market, has created a new set of opportunities for companies to develop new publicity strategies. One of the most widespread forms of engaging mobile users from printed materials is based on the use of QR codes, which have been adopted for many different applications such as accessing web sites or downloading premium content. In this research work, we will be performing embedding QR code into color image and hiding information using QR code, in order to make them visually appealing to the user while maintaining acceptable decoding robustness. In contrast to previous approaches the methods presented here allows to automatically embedding QR codes into color, grayscale or binary images. These embedding are designed to be compatible with standard decoding applications and can be applied to any color image with full area coverage. The embedding problem is solved by the integration of halftoning method. Finally, we show experimental results of halftoning of color image, embedded QR code image in color image and decoded QR code image from color is connected to the internet with a sensor for understanding the property of the thing for which a two-dimensional code was used. Two-dimensional codes can play the role of connecting cyberspace to physical space, and can play a significant role in the so-called Internet of Things. Moreover, the advancement of machine vision is progressing with machine-to-machine communication. On the other hand, there is also private information, such as personal information, that should not be known by others. Current two-dimensional codes have become ubiquitous and express the cell using two colors white and black. The cell expresses white or black in one bit, and there is no confidentiality available. In response to this, we propose an addition to the existing part that can be read with conventional equipment. We propose a 'secrecy part' that cannot be read without a decryption key. Further, we propose a method for rendering these two-dimensional codes compatible with black-and-white codes. In order to generate the secrecy part, it is necessary to transform a cell into several bits. A multicolor method and a multiple-region method are used to transform the code into several bits. An evaluation of the multi-valued cells in the two-dimensional codes here proposed, with a read verification and compatibility along with the added secrecy part, was carried out using a smartphone with successful Zhang Tiegang GaoQuick Response Code QR Code has become an important entrance of O2O Online to Offline in the era of mobile internet. Many applications, such as transformation of URLs, the descriptions of these images, and so on can be realized through embedding QR Code into images. However, the embedding of QR Code may destroy some image details in the corresponding area, which is annoying, especially in these applications that need high precision. The reversible recovery of original image is of importance. A reversible visible watermarking scheme is proposed for embedding QR Code into images. One can decode the information that is encoded in the QR Code and reversibly recover the original image after the QR Code is scanned successfully. Optimization has been achieved both by utilizing the features of QR Code when encoding and decoding in the visible watermarking period and by utilizing the blocking, scanning, and preprocessing of information in the reversible data hiding period. Experimental results have demonstrated the validity and efficiency of the proposed scheme. Better image quality has been achieved by the proposed scheme compared with existing QR code based blind digital image watermarking technique with an attack detection feature is described here. The technique describes a key based framework to incorporate image, server port address or website address as watermark data; which increases the extended usability of the embedded data and the adaptability of the verification application. The watermarking problem is formulated as a signal communication problem with watermark data representation, embedding of watermark and attack detection as a source encoding, channel encoding and attenuation detection problems respectively. The mathematical aspects of the respective signal processing problems are extended to digital image watermarking with sufficient background support. The use of QR code ensures extended usability, while the application specific watermark data achieves adaptability of the verification application. The QR code is embedded into the attack resistant HH component of 1st level DWT domain of the cover image and to detect malicious interference by an attacker, a unique image registry code generated from the high frequency structural components of the stego-image is used. The key based approach and the attack resistant embedding domain makes this method robust against visually invariant attacks. The testing results show the compliance of the method with all the proposed WangThis paper presents a novel image trading mechanism based on hybrid watermarking techniques. The removable visible watermarking technique is used to provide the safe preview of the protected media. The fingerprinting is used to trace the illegal distributor. Two kinds of watermarking techniques embed watermarks in DCT domain in order to conform to compression techniques. Experimental results show that image trading mechanism based on hybrid watermarking techniques can protect the image with high technologies are now charring a vital role in our day to day life. It has the advantages along with the disadvantages also, which in term generates the requirements of information hiding technology for maintaining the secrecy of the secret information. Extensive amount of work has been carried out by different researchers in this field. In this paper, a novel special domain image Steganography method has been proposed which has been design based as an extension of the PMM method. C 2013 The Authors. Published by Elsevier novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio PSNR of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed this paper, we present two new methods for authentication of digital images using invertible watermarking. While virtually all watermarking schemes introduce some small amount of non-invertible distortion in the image, the new methods are invertible in the sense that, if the image is deemed authentic, the distortion due to authentication can be removed to obtain the original image data. Two techniques are proposed one is based on robust spatial additive watermarks combined with modulo addition and the second one on lossless compression and encryption of bit-planes. Both techniques provide cryptographic strength in verifying the image integrity in the sense that the probability of making a modification to the image that will not be detected can be directly related to a secure cryptographic element, such as a has function. The second technique can be generalized to other data types than bitmap to quantization error, bit-replacement, or truncation, most data embedding techniques proposed so far lead to distortions in the original image. These distortions create problems in some areas such as medical, astronomical, and military imagery. Lossless watermarking is an exact restoration approach for recovering the original image from the watermarked image. In this paper we present a novel reversible watermarking technique with higher embedding capacity considering the Human Visual System HVS. During embedding we detect the textured blocks, extract LSBs of the pixel-values from these textured blocks considering the HVS and concatenate the authentication information with the compressed bit-string. We then replace the LSBs of the textured blocks considering the HVS with this bit-string. Since we consider the HVS while extracting LSBs and embedding the payload, the distortions in the resulting watermarked image are completely reversible and imperceptible. We present experimental results to demonstrate the utility of our proposed visible watermark may convey ownership information that identifies the originator of image and video. A potential application scenario for visible watermarks was proposed by IBM where an image is originally embedded with a visible watermark before posting on the web for free observation and download. The watermarked image which serves as a "teaser." The watermark can be removed to recreate the unmarked image by request of interested buyers. Before we can design an algorithm for satisfying this application, three basic problems should be solved. First, we need to find a strategy suitable for producing large amount of visually same but numerically different watermarked versions of the image for different users. Second, the algorithm should let the embedding parameters reachable for any legal user to make the embedding process invertible. Third, an unauthorized user should be prevented from removing the embedded watermark pattern. In this letter, we propose a user-key-dependent removable visible watermarking system RVWS. The user key structure decides both the embedded subset of watermark and the host information adopted for adaptive embedding. The neighbor-dependent embedder adjusts the marking strength to host features and makes unauthorized removal very difficult. With correct user keys, watermark removal can be accomplished in "informed detection" and the high quality unmarked image can be restored. In contrast, unauthorized operation either overly or insufficiently removes the watermark due to wrong estimation of embedding parameters, and thus, the resulting image has apparent data hiding, distortions are introduced in an original image because of quantization errors, bit-replacement, or truncation at the grayscale limit. These distortions are irreversible and visible which are unacceptable in some applications like medical imaging. However, the reversible watermarking technique overcomes this problem by retrieving the original image from the watermarked image. In this paper, we present a novel reversible watermarking algorithm with a high embedding capacity considering the human visual system HVS. We use the arithmetic coding technique to compress a part of the original image and store the compressed data together with necessary authentication information as the payload. The payload is then embedded within the original image with consideration of the HVS. Due to this, the watermarked image contains no perceptible artifacts. During the extraction phase, we extract the payload, restore the exact copy of the original image and verify the authenticity. Experimental results show that our method provides a higher embedding capacity compared to the other algorithms proposed in the common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small and perceptual models are used to minimize its visibility, the distortion may not be acceptable for medical imagery for legal reasons or for military images inspected under non-standard viewing conditions after enhancement or extreme zoom. In this paper, we introduce a new paradigm for data embedding in images lossless data embedding that has the property that the distortion due to embedding can be completely removed from the watermarked image after the embedded data has been extracted. We present lossless embedding methods for the uncompressed formats BMP, TIFF and for the JPEG format. We also show how the concept of lossless data embedding can be used as a powerful tool to achieve a variety of non-trivial tasks, including lossless authentication using fragile watermarks, steganalysis of LSB embedding, and distortion-free robust based scaling of a watermark image is of paramount importance to make the degree of marking applied variable according to the features of host images. Here. A wavelet domain visible watermarking is proposed. The scaling factors for the pixel based method are adaptively determined by the effect of luminance and local spatial characteristicsIn this paper, we propose a reversible visible watermarking algorithm to satisfy a new application scenario where the visible watermark serves as a tag or ownership identifier, but can be completely removed to resume the original image data. It includes two procedures data hiding and visible watermark embedding. In order to losslessly recover both the watermark-covered and nonwatermark-covered image contents at the receiver end, the payload consists of two reconstruction data packets, one for recovering the watermark-covered region, and the other for the nonwatermark-covered region. The data hiding technique reversibly hides the payload in the image region not covered by the visible watermark. To satisfy the requirements of large capacity and high image quality, our hiding technique is based on data compression and uses a payload-adaptive scheme. It further adopts error diffusion for improving subjective image quality and arithmetic compression using a character-based model for increasing computational efficiency. The visible watermark is securely embedded based on a user-key-controlled embedding mechanism. The data hiding and the visible watermark embedding procedures are integrated into a secure watermarking system by a specially designed user key Jun TianReversible data embedding has drawn lots of interest recently. Being reversible, the original digital content can be completely restored. We present a novel reversible data-embedding method for digital images. We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low. Bian YangZheming LuShenghe SunMany watermarking algorithms have been proposed based on the vector quantization VQ technique, which bases the watermark embedding and extracting schemes on the idea of quantization index modulation QIM. We review in this paper VQ-based watermarking algorithms regarding the reversibility of VQ indices in the compressed domain. Considering the reversibility is usually traded with the compression performance, we propose a new reversible image watermarking algorithm using a modified version of the traditional fast correlation based VQ FCVQ and achieves both higher compression and watermarking performance than other algorithms. The advantages of the proposed modified FCVQ include the desirable compression performance and the independently applicability in the practical case without watermarking. Simulation results demonstrated our proposed algorithm. Comparisons between our algorithm and others are this paper, we propose a new algorithm in reversible data hiding, with the application associated with the quick response QR codes. QR codes are random patterns, which can be commonly observed on the corner of posters or webpages. The goal of QR codes aims at convenienceoriented applications for mobile phone users. People can use the mobile phone cameras to capture QR code at the corner of web page, and then the hyperlink corresponding to the QR code can be accessed instantly. Since QR code looks like random noise and it occupies a corner of the original image, its existence can greatly reduce the value of the original content. Thus, how to retain the value of original image, while keeping the capability for the instant access for webpages, would be the major concern of this paper. With the aid of our reversible data hiding technique, the QR codes can be hidden into the original image, and considerable increase in embedding capacity can be expected. Next, we propose a scheme such that when the image containing the QR code is browsed, the hyperlink corresponding to the QR code is accessed first. Then, the QR code could get vanished and the original image would be recovered to retain the information conveyed therein. Simulation results demonstrate the applicability of the proposed novel reversible data hiding scheme based on invariability of the sum of pixel pairs and pairwise difference adjustment PDA is presented in this letter. For each pixel pair, if a certain value is added to one pixel while the same value is subtracted from the other, then the sum of these two pixels will remain unchanged. How to properly select this value is the key issue for the balance between reversibility and distortion. In this letter, half the difference of a pixel pair plus 1-bit watermark has been elaborately selected to satisfy this purpose. In addition, PDA is proposed to significantly reduce the capacity consumed by overhead information. A series of experiments is conducted to verify the effectiveness and advantages of the proposed Yang Ming-Han TsaiData hiding is an important way of realising copyright protection for multimedia. In this study, a new predictive method is proposed to enhance the histogram-based reversible data hiding approach on grey images. In those developed histogram-based reversible data hiding approaches, their drawbacks are the number of predictive values less to the number of pixels in an image. In these interleaving prediction methods, the predictive values are as many as the pixel values. All predictive error values are transformed into histogram to create higher peak values and to improve the embedding capacity. Moreover, for each pixel, its difference value between the original image and the stego-image remains within ±1. This guarantees that the peak signal-to-noise ratio PSNR of the stego-image is above 48±dB. Experimental results show that the histogram-based reversible data hiding approach can raise a larger capacity and still remain a good image quality, compared to other histogram-based LiuWen-Hsiang TsaiA novel method for generic visible watermarking with a capability of lossless image recovery is proposed. The method is based on the use of deterministic one-to-one compound mappings of image pixel values for overlaying a variety of visible watermarks of arbitrary sizes on cover images. The compound mappings are proved to be reversible, which allows for lossless recovery of original images from watermarked images. The mappings may be adjusted to yield pixel values close to those of desired visible watermarks. Different types of visible watermarks, including opaque monochrome and translucent full color ones, are embedded as applications of the proposed generic approach. A two-fold monotonically increasing compound mapping is created and proved to yield more distinctive visible watermarks in the watermarked image. Security protection measures by parameter and mapping randomizations have also been proposed to deter attackers from illicit image recoveries. Experimental results demonstrating the effectiveness of the proposed approach are also Tsai Yu-Chen HuHsiu-Lien YehIn this paper, a reversible image hiding scheme based on histogram shifting for medical images is proposed. As we know, the histogram-based reversible data hiding is limited by the hiding capacity, which is influenced by the overhead of position information that has to be embedded in the host image. To solve this problem, the similarity of neighboring pixels in the images was explored by using the prediction technique and the residual histogram of the predicted errors of the host image was used to hide the secret data in the proposed scheme. In addition, the overlapping between peak and zero pairs was used to further increase the hiding to the experimental results, a higher hiding capacity was obtained and a good quality stego-image was preserved in the proposed scheme. The hiding capacity provided by the proposed scheme was approximately three times that of the original histogram-based method. Compared to the histogram-based method, the quality of the stego-image improved about dB when the same amounts of secret data were TsaiA novel visible watermarking algorithm based on the content and contrast aware COCOA technique with the consideration of Human Visual System HVS model is presented in this study. In order to determine the optimal watermark locations and strength at the watermark embedding stage, the COCOA visible watermarking utilizes the global and local characteristics of the host and watermark images in the discrete wavelet transform DWT domain. To achieve the best tradeoff between the embedding energy of watermark and the perceptual translucence, the utilization of contrast–sensitive function, noise visible function of perceptual model, and the basis function amplitudes of DWT coefficients are fine tuned, for the best quality of perceptual translucence and noise reduction of the COCOA algorithm. The experimental results demonstrate that COCOA technique not only provides high PSNR values for the watermarked images, but also preserves the watermark visibility under various signal processing operations, especially the watermark removal LuJun-Xiang WangBei-Bei LiuCopyright protection and information security have become serious problems due to the ever growing amount of digital data over the Internet. Reversible data hiding is a special type of data hiding technique that guarantees not only the secret data but also the cover media can be reconstructed without any distortion. Traditional schemes are based on spatial, discrete cosine transformation DCT and discrete wavelet transformation DWT domains. Recently, some vector quantization VQ based reversible data hiding schemes have been proposed. This paper proposes an improved reversible data hiding scheme based on VQ-index residual value coding. Experimental results show that our scheme outperforms two recently proposed schemes, namely side-match vector quantization SMVQ-based data hiding and modified fast correlation vector quantization MFCVQ-based data TsengChi-Pin HsiehFor some applications such as satellite and medical images, reversible data hiding is the best solution to provide copyright protection or authentication. Being reversible, the decoder can extract the hidden data and recover the original image without distortion. In this paper, a reversible data hiding scheme based on prediction error expansion is proposed. The predictive value is computed by using various predictors. The secret data is embedded in the cover image by exploiting the expansion of the difference between a pixel and its predictive value. Experimental results show that our method is capable of providing a great embedding capacity without making noticeable distortion. In addition, the proposed scheme is also applicable to various TsaiLong-Wen ChangA novel reversible visible watermarking algorithm is proposed. It can fully remove the watermark from the visible watermarked image such that the original image can be restored. Pixel values of original image beneath the watermark are mapped to a small range [alpha, alpha + 127] to generate a visible watermarked image. Since the mapping is many-to-one, taking inverse mapping can only approximate the original image. To restore the original image, the difference image of subtracting the approximated image from the original image and other side information are losslessly compressed to be embedded in the visible watermarked image by a reversible data embedding algorithm. We proposed a key-based scheme for the compromise between transparency and robustness. The key is a random variable with discrete normal distribution. In addition, only users with correct key can restore the original image. In the experimental results, we show the transparent degree of watermark can be controlled by the variance of the key. Users with wrong key can not restore the original image from the visible watermarked XiantingPing LingdiLi ZhuoThis paper presents a reversible data hiding scheme. The proposed scheme is based on the difference histogram shifting to spare space for data hiding. Nine basic scan paths are defined, and this means all-directional adjacent pixel differences can be obtained. Due to the fact that the grayscale values of adjacent pixels are close to each other, the all-directional adjacent pixel difference histogram contains a large number of points with equal values. Hence, more data can be embedded into the cover image than previous works based on histogram shifting. Furthermore, multi-layer embedding is used to increase the hiding capacity. In each embedding process, we can embed a large number of data into the cover image by choosing the best scan path and the optimized pixel difference. As experimental results have shown, the cover images are able to embed secret data at an average of the size of the original images while all the PSNR values of the stego images remain larger than 30 novel reversible data hiding scheme based on an integer transform is presented in this paper. The invertible integer transform exploits the correlations among four pixels in a quad. Data embedding is carried out by expanding the differences between one pixel and each of its three neighboring pixels. However, the high hiding capacity can not be achieved only by difference expansion, so the companding technique is introduced into the embedding process so as to further increase hiding capacity. A series of experiments are conducted to verify the feasibility and effectiveness of the proposed watermarking is an important intellectual property rights IPR protection technique for digital images. For some purposes such as contents used in learning web sites or digital libraries, digital images have to be released but illegal reproductions of them are prohibited. Digital images embedded with visible watermarks will contain perceptible but unobtrusive patterns. The embedded patterns should be difficult to be removed unless intensive and expensive human labors are involved. Recently, Huang and Wu have proposed an attacking scheme against visible watermarks. The structure of embedded visible watermark will be seriously destroyed and a perceptually satisfying recovered image can be obtained by this attacking scheme. To improve the robustness of current visible watermarking schemes, a novel scheme that takes advantages of visible watermarking, fragile watermarking and information hiding has been studied in our research. Simulation results demonstrate that our scheme is robust to the present attacking scheme for visible M. AlattarA reversible watermarking algorithm with very high data-hiding capacity has been developed for color images. The algorithm allows the watermarking process to be reversed, which restores the exact original image. The algorithm hides several bits in the difference expansion of vectors of adjacent pixels. The required general reversible integer transform and the necessary conditions to avoid underflow and overflow are derived for any vector of arbitrary length. Also, the potential payload size that can be embedded into a host image is discussed, and a feedback system for controlling this size is developed. In addition, to maximize the amount of data that can be hidden into an image, the embedding algorithm can be applied recursively across the color components. Simulation results using spatial triplets, spatial quads, cross-color triplets, and cross-color quads are presented and compared with the existing reversible watermarking algorithms. These results indicate that the spatial, quad-based algorithm allows for hiding the largest payload at the highest signal-to-noise is composed of the one-bit pixel on the IK. The constitution of Stem starts at Stem = 1. Step 5If S is found, then compress Stem before each addition and stratify If not, repeat step 5Dc= StemStemStep 4To find out S via Stem, which is composed of the one-bit pixel on the IK. The constitution of Stem starts at Stem = 1. Step 5If S is found, then compress Stem before each addition and stratify DC = Stem − Stem,c . If not, repeat step 5. Step 6Construct the payload bit stream as H = SC ɷ DC. Replace S with H to create I – Rm. REFERENCES In the modern era of virtual computers over the notional environment of computer networks, the protection of influential documents is a major concern. To bring out this motto, digital watermarking with biometric features plays a crucial part. It utilizes advanced technology of cuffing data into digital media, text, image, video, or audio files. The strategy of cuffing an image inside another image by applying biometric features namely signature and fingerprint using watermarking techniques is the key purpose of this study. To accomplish this, a combined watermarking strategy consisting of Discrete Wavelet Transform, Discrete Cosine Transform, and Singular Value Decomposition DWT-DCT-SVD is projected for authentication of image that is foolproof against attacks. Here, singular values of watermark1 fingerprint and watermark2 signature are obtained by applying DWT-DCT-SVD. Affixing both the singular values of watermarks, we acquire the transformed watermark. Later, the same is applied to cover image to extract the singular values. Then we add these values to the cover image and transformed watermark to obtain a final watermarked image containing both signature and fingerprint. To upgrade the reliability, sturdiness, and originality of the image, a fusion of watermarking techniques along with dual biometric features is exhibited. The experimental results conveyed that the proposed scheme achieved an average PSNR value of about 40 dB, an average SSIM value of and an embedded watermark resilient to various attacks in the watermarked IntroductionCopyright infringement has increased as a result of the rapid blooming of cyberspace and communication technology, which has led to an exchange of digital mixed media content. The transmission of digital data across public networks like the Internet makes the protection of personal information and intellectual property rights IPR crucial in the modern day [1]. Digital watermarking is a means to get around this problem and prove ownership of digital assets that are being used ease of multimedia content distribution is due to the fast development of the internet, multimedia technologies, communication, and reproduction. Multimedia data is prone to issues such as illegal copying and distribution pirating, editing, and copyright. In order to protect the data from the above-mentioned issues, digital watermarking is encrypted sort of coding called a digital watermark is added to a signal that can handle sounds, such as audio, video, or image data. Biometric systems have been using watermarking techniques to safeguard and authenticate biometric data and improve recognition accuracy in an effort to boost the trustworthiness of self-awareness systems that can be differentiated between a legitimate person and a fraudster. An encrypted sort of coding called a digital watermark is added to a signal that can handle sounds, such as audio, video, or image data. Biometric systems have been using watermarking techniques to safeguard and authenticate biometric data and improve recognition accuracy in an effort to boost the trustworthiness of self-awareness systems that can tell the difference between a legitimate person and a proposed work briefs on how to authenticate images by embedding biometric information into a digital image using a new hybrid system that includes three different algorithms namely DWT-DCT-SVD. In the embedding process, the cover image undergoes a DWT transform which decomposes it into four subbands, namely, L-L, L-H, H-L, and H-H, where L-L denotes Low-Low, L-H denotes Low-High, H-L denotes High-Low, H-H denotes High-High. L-L subband undergoes DCT transform to obtain 4 × 4 blocks. The DCT transform mainly compresses the data or image. The SVD of a matrix is an orthogonal transform used for matrix diagonalization to obtain singular values of the watermark. Subsequently, the SVD factors of each block are modified to create the watermarked image, extracted, and then inserted into the cover image. In the process of extraction, the watermarked image is acquired and a reverse stratagem is utilized to obtain the watermark, which is the biometric refers to the automatic identification of people based on their physiological and behavioral features; two authentications based on behavioral and physiological characteristics for attaching the watermark to the cover image are applied. Measurements taken from the human body are used in physiological biometrics, such as fingerprints, iris, face, retina. The dynamic measurements used in behavioral biometrics such as signatures, voice, and keystrokes, are based on human actions. The proposed hybrid watermarking system is cooperative integration of signature and fingerprint watermarks to cover image to assure the integrity, authenticity, and confidentiality of the digital documents. The embedding procedure consists of two steps in the projected method. First, the embedding of the signature in the fingerprint is carried out to create the transformed watermark, as shown in Figure 1. The final watermark is created by embedding the cover image in this extraction procedure is split into two steps. Step 1 extract the fingerprint from the watermark that results in an extracted fingerprint. Step 2 the signature is further extracted from the extracted fingerprint image, as shown in Figure Hybrid DWT-DCT-SVDThe proposed scheme consists of DWT, DCT, and SVD for image authentication that is robust against attacks. In the process of watermarking, two major steps are carried out viz., embedding and extraction. In this, the combinations of DWT, DCT, and SVD along with their inverses are applied. This hybrid technique is suitable for different image processing attacks by achieving the properties of watermarks, integrity, authenticity, and confidentiality of digitized image documents. The performance metrics used in this research are Peak Signal to Noise Ratio PSNR, Structural Similarity Index SSIM, and Normalized Correlation NC. This proposed methodology is deployed on dual watermarking where the embedding process consists of DWT, DCT, and SVD which provide image authentication and is robust against embedding process consists of DWT, DCT, and SVD watermarking techniques. To cover the image, one level of DWT is applied. Hence applied SVD to the L-L sub-band. Besides, the application of DWT to the biometric and then DCT followed by the SVD technique is carried out. Parallelly, SVD is applied to the signature. Application of SVD to the images results in three matrices namely U S and V. Considered the singular valued S matrix as it contains the diagonal properties of the image. Further, added the singular values of the biometric and alpha times of the signature. To recreate the L-L sub-hand of biometric the inverse of the SVD is applied. Later, we applied inverse DCT as we applied DCT in the earlier steps. Now we have applied inverse DWT to create an image with a modified L-L subband. This gives a results in the transformed watermark. Now apply the application of SVD to it in order to get a singular valued matrix. Next, to cover the image, singular values are added off and beta times singular matrix of the transformed watermark. Now apply the inverse SVD to recreate the cover image with manipulated singular values. Then followed by applying DCT and then DWT to create an image with a modified L-L subband. This gives a final watermarked image; this contains the signature and biometric embedded on the cover image, and this completes the embedded process. The extraction process for the transformed watermark biometric is done by applying DWT on the final watermark to obtain four subbands. Next, apply DCT to the L-L sub-band followed by SVD to obtain singular values of final watermarked image. Later, DWT is followed by DCT and then SVD to obtain signature images from the transformed image. This completes the extraction DCTWhen digital photos are uncompressed, they require a massive quantity of storage space. For such uncompressed data to be transmitted across the network, large transmission bandwidth is required. The most common image compression method is the Discrete Cosine Transform DCT [1]. The JPEG picture compression method makes use of DCT. The two-dimensional DCT is calculated for each block of the 8 × 8 or 16 × 16 divided input image. Following that, the DCT coefficients are quantized, encoded, and DCT can store the image with only fewer coefficients, and is used in lossy image compression to reduce the redundancy between neighboring pixels. The DCT formula with a 2D matrix is shown in equation 1.where the x, yth elements of the image element are represented by the matrix p as px, y. The block’s size, N, is used for the DCT. The pixel values of the native matrix of the image equation determine the value of one entry i, jth of the modified image. For the standard JPEG 8 × 8 blocks, N = 8 and x, y is in the stretch of 0 to DCT divides pictures into components with various frequencies. Because fewer significant frequencies are dropped during quantization in the compression portion, the term lossy is in use. Later, during the decompression phase, the image is retrieved using the remaining most crucial frequencies. As a result, some distortion is included in the reconstructed images; however, the levels of distortion can be altered during the compression stage. JPEG is used for both color and black and white photographs; however, the article focuses on the DWTThe suggested methodology incorporates the Discrete Wavelet Transform DWT [2] approach to withstand the attacks with a robust model. Low-Low, Low-High, High-Low, and High-High, L-L, L-H, H-L, and H-H are four subbands created by DWT HH. The original image will be recreated using the above four subbands. The image can theoretically be processed via the filter bank as shown in Figure 3 to produce various subband frequency illustrated in Figure 4, the L-L subband defines low-pass filtering for each row and column, resulting in a low-resolution approximation of the original image. Similarly, the L-H subband was created by applying low-pass filtering to each row and high-pass filtering to each column. The L-H subband is influenced by high-frequency features along the column direction. The H-L subband is the result of high-pass and low-pass filtering on each row and column. The H-L subband is influenced by high-frequency features along the row direction. The H-H subband is created by applying high-pass filtering to each row and column. The H-H subband is influenced by high-frequency features in the diagonal direction [3].DWT-Based Feature Extraction using multilevel decomposition of previously processed pictures, DWT effectively extracts discriminant characteristics that are impervious to arbitrary environmental fluctuations. The discrete interval wavelets are sampled for the wavelet transform known as the DWT. DWT provides information about the frequency and spatial domains of a picture simultaneously. An image can be studied using the DWT operation, which combines the analysis filter bank and decimation process. A 2D transform is created from two distinct 1D transformations. In 1D DWT, the approximation coefficients hold the low-frequency information, whereas the detail coefficients hold the high-frequency information. The input image is divided into four separate subbands by the application of 2D DWT low-frequency components in the horizontal and vertical directions cA, low-frequency components in the horizontal and high-frequency components in the vertical directions cV, high-frequency components in the horizontal and low-frequency components in the vertical directions cH, and high-frequency components in the horizontal and vertical directions cD. You can alternatively write cA, cV, cH, and cD as L-L, L-H, H-L, and H-H, SVDSingular value decomposition SVD [1, 4] is a method for approximating data matrix decomposition into an optimal approximation of the signal and noise components. This is one of the most essential aspects of the SVD decomposition in noise filtering, compression, and forensics, and it can also be viewed as a properly identifiable noise refactors into three matrices for the given digital image. To refactor the image singular values are used and at the end of this process storage space required by the image is reduced as the image is represented with a smaller set of values. The SVD of M × N matrix A is given by the following equation 2.where U M × N matrix of the orthonormal eigenvectors of AAT. 𝑉𝑇 Transpose of the n × n matrix containing the orthonormal eigenvectors of A^{T}A. W N × N diagonal matrix of the singular values which are the square roots of the eigenvalues of system can be divided into a number of linearly independent components, each of which contributes its own amount of energy, using the most efficient and stable technique known as orthogonal matrix columns U are referred to as the left singular vectors, whereas the orthogonal matrix columns V are referred to as the right singular vectors. The diagonal members are reflecting the singular values of the maximum energy packing of the SVD, the ability to solve the least squares issue, the ability to compute the pseudoinverse of a matrix, and multivariate analysis are all significant benefits for images [1, 5]. A crucial characteristic of SVD is its relationship to a matrix’s rank and its capacity to approximate matrices of a particular rank. Digital images can frequently be characterized by the sum of a relatively limited number of Eigen images since they are frequently represented by low-rank matrices. Images are compressed in compression, and SVD with the highest energy packing property is typically used. As previously established, SVD divides a matrix into orthogonal parts so that the best sub-rank approximations can be made [6, 7]. Truncated SVD transformation with rank r offers significant storage savings over storing the entire matrix with acceptable quality. The block diagram for the SVD-based compression is shown in Figure illumination data can be found in the singular value matrix produced by SVD. As a result, altering the single values will directly impact how the image is illuminated. As a result, the image’s other details won’t be altered. Second, by using the L-L subband illumination enhancement, the edge information in other subbands will be protected L-H, H-L, and H-H.The study [1] the research that is being offered displays an adaptive scaling factor based on particular DWT-DCT coefficients of its image material. The role of particular DWT-DCT coefficients relative to the average value of DWT-DCT coefficients was used to construct the adaptive scaling factor. Using a suggested set of guidelines that consider the adaptive scaling factor, the watermark image was integrated. The results of the experiments showed that the suggested method produced a high PSNR value of 47 dB, an SSIM value of around and an implanted watermark resistance to many attacks in the watermarked the integration procedure in the article [5], a discrete wavelet transform is applied to the image, and then the ZigZag scanning method is used to topologically reorganize the coefficients of the L-L subbands. The watermark bits are then integrated using the resulting coefficients. The integrity of the watermark may be easily confirmed thanks to an embedded hash of the electronic patient record. The experimental results show that the approach has high invisibility with a PSNR above 70 dB and very good robustness against a wide range of geometric and destructive attacks. The invisibility and robustness of the approach have been many of the currently used hybrid SVD-based picture watermarking systems is insecure, the study [4] primarily focuses on the analysis of the state-of-the-art in this area. Additionally, there aren’t many in-depth reviews in this field. In order to draw attention to numerous security risks, unresolved challenges, and research gaps, they conducted efficiency comparisons. Based on the results, this study gives researchers and practitioners important information they can use to improve the field of picture watermarking. It also gives suggestions for how to make more reliable schemes in the work [8] achieved a superior imperceptibility of dB, and demonstrates that watermarking may be included in a host image using various transform operations, including discrete cosine transform DCT, discrete wavelet transforms DWT, and singular value decomposition SVD. But not every design criterion is met at once by a single transformation. In order to close this gap, they developed a hybrid blind digital image watermarking technique using DCT, DWT, and SVD. This method was more robust than existing state-of-the-art techniques against filter, salt-and-pepper noise SPN, and rotation attacks. The WNC value for a median filter with various window sizes is 1, which is higher than the current well-known transforms—the discrete wavelet transform DWT, discrete cosine transform DCT, and singular value decomposition—are combined in the system in [6] SVD. By reaching greater values of imperceptibility in the form of PSNR with a value of decibels dB and SSIM with a value of experimental results show that the suggested technique exceeds the strategies already published in the literature. With a maximum NCC value of and a minimum BER value of it simultaneously achieves exceptional robustness ratings. The DWT-SVD performance suggested in the study [9] was verified throughout the training phase, and the suggested system’s high invisibility and resilience against different forms of attacks on watermarked photos were also demonstrated. When the suggested system’s findings were contrasted with those of other systems, it became clear that DWT-SVD performed better against pixel-value alteration suggested work in [10] illustrates a robust watermarking technique for grayscale photos using lifting wavelet transform and singular value decomposition as the basis for multiobjective artificial bee colony optimization. Here, the actual image is changed to four subbands using three levels of lifting wavelet transform, and then the watermark image’s singular value is merged with the original image’s unique value for the L-H subband. In order to achieve the highest possible robustness without compromising watermark clarity, multiple scaling factors are used in the embedding operation on behalf of the single scaling element. The results of the experiments show that the invisibility is very good and that it is resistant to a wide range of attacks that use image processing. A non-blind watermarking NBW schemes malfunction for watermarking stratagem thereby giving out to impart perpetually imperceptibility, depriving of robustness and competence for embedding. So, to tame this drawback, an algorithm for blind watermarking BW was proposed [11] to cover the glitches of impart safeguarding of copyright that has crucial demand for color images, an image-watermarking scheme deployed on sequence-based MRT SMRT was tendered for color images [12] where the principle goal was to detect preferable color space among the habitually pre-owned color spaces. A cascaded neural network approach deployed on two different neural network models was projected [13] by using an optimized feature-based digital watermarking algorithm. Here, the cascading of the neural network spawns the potent pattern for embedding. In the study [14], researchers tendered a strategy using watermarking technique of Fourier transform for color images where image will be declined into two variants where the image is segmented into R, G and B, sections where DFT is performed and these coefficients so obtained will use medium frequency band to encapsulate [15], which comprises of discrete wave transformation technique combined with Hessenberg decomposition HD and singular value decomposition SVD using scaling factor, watermark is embedded into the cover image. In [16], a watermarking algorithm of the color image is projected, where it explores the combination of DWT-DCT-SVD. Here the host image which is in RGB space is converted to YUV color space. Then a layer of DWT is put into the luminance component Y, followed by DCT and SVD to each block. The results are good enough to embrace the attacks and imperceptibility property of watermark. In [2, 3, 7, 17], some basic comparison of watermarking with steganography and a summary of different methods of image steganography is carried out. An effective DWT–SVD is deployed with self-adaptive differential evolution SDE algorithm for image watermarking scheme, SDE adjusts the mutation factor F and the crossover rate Cr dynamically in order to balance an individual’s exploration and exploitation capability for different evolving phases to achieve invisibility [18–20]. In [21–24], comparative analysis of image compression is done by three transform methods, which are Discrete Cosine Transform DCT, Discrete Wavelet Transform DWT and Hybrid DCT + DWT Transform, thereby achieving better invisibility property and good PSNR Proposed MethodologyThis proposed methodology is deployed on dual watermarking where the embedding process consists of DWT, DCT, and SVD which provide image authentication and is robust against attacks. Figure 6 depicts the embedding process that consists of DWT, DCT, and SVD watermarking techniques. The two watermarks used in the proposed methodology are biometrics and signature. These images are converted in grayscale because the SVD can only be applied to two-dimensional images whereas the color images are of three dimensions. Since the property of DWT after one level decomposition, the host image should be larger than the watermark. For the first embedding process, biometrics is the host image and the signature is the watermark. The biometric should be larger than the signature. Here, to the cover image one level of DWT is applied. Then the image is divided into four subbands, namely, L-L, L-H, H-L, and H-H. The major details and properties of the image are stored in the L-L subband. So, we contemplate embedding the biometric into the L-L subband. So, we have applied SVD to the L-L subband. Besides we have applied DWT to the biometric and then DCT and followed by SVD. Parallelly, we applied SVD to the signature, by applying SVD to the images we obtain three matrices namely U S and proposed methodology is divided into two steps Embedding Extraction Watermark Embedding AlgorithmThe Embedding algorithm can be split into two phases process of signature into biometric Step 1 Apply SVD to the signature to obtain the singular values SVS. Step 2 Apply DWT level-1 to the biometric to obtain 4-subbands. Step 3 Apply DCT to L-L subband in order to remove redundancy. Step 4 Apply SVD to the biometric to obtain singular values SVB. Step 5 Change the singular values of biometric SVB by adding the singular values of signature SVS. Step 6 The Transformed watermark TW is obtained by applying inverse SVD, DCT and process of Transformed watermark into Cover image Step 1 Apply DWT to cover image to obtain 4-subbands. Step 2 Apply DCT to L-L subband in order to remove redundancy. Step 3 Apply SVD to obtain the singular values of cover image SVC. Step 4 Manipulate the singular values of cover image SVC by adding the singular values of transformed image SVTW. Step 5 Obtain the final watermarked image by applying the inverse of SVD, DCT, and DWT techniques on the modified Extraction ProcessFigure 7 depicts the extraction process, which is the extraction of watermarks, biometric and signature from the cover image. The extraction is carried out as follows of Transformed watermark biometric Step 1 Apply DWT on the final watermark to obtain four subbands. Step 2 Apply DCT to L-L subband in order to remove redundancy. Step 3 Apply SVD to obtain the singular values of the final watermarked image SVFW. Step 4 To obtain the transformed watermark image, subtract the singular values of final watermarked image SVFW from the cover image singular values SVC. and divide the whole with the beta of signature watermark from transformed watermark biometric Step 1 Apply DWT on transformed watermark to obtain four subbands. Step 2 Apply DCT to L-L subband in order to remove redundancy. Step 3 Apply SVD to obtain the singular values of the transformed watermark. Step 4 To obtain a signature, subtract the singular values of transformed watermark SVTM from the biometric singular values SVB. and divide the whole with the alpha Experimental ResultsThe outcome of the projected technique discloses a hybrid combination of DWT-DCT-SVD that gives the best NC values along with good PSNR and SSIM. By applying DWT alone, the host image doesn’t withstand a few attacks. So, by introducing DCT, it has the ability to pack most of the information in the fewest coefficients thereby reducing the redundancy between the neighboring pixels. By using SVD, it makes it easier to hide the image. This combination works for all sorts of attacks and also gives better Figure 8, a watermarked image of size 512 × 512 has been subjected to various watermarking attacks, including Gaussian low-pass filter, Median, Salt and Pepper noise, Speckle noise, JPEG compression, Sharpening attack, Histogram equalization, Average filter, Gaussian noise, JPEG2000 compression, and Motion blur. It was robust against all of these attacks. Figure 9 shows an extracted fingerprint of size 256 × 256. When the cover image is subjected to various watermarking attacks such as Gaussian low-pass filter, Median, Salt and Pepper noise, Speckle noise, JPEG compression, Sharpening attack, Histogram equalization, Average filter, Gaussian noise, JPEG2000 compression, and Motion blur. It is resistant to all of these Figure 10, the cover image is subjected to various watermarking attacks, such as the Gaussian low-pass filter, Median, Salt and Pepper noise, Speckle noise, JPEG compression, sharpening attack, Histogram equalization, Average filter, Gaussian noise, JPEG2000 compression, and Motion blur, an extracted signature of size 128 × 128 is displayed. It resisted all of these attacks. The graph of SSIM versus scaling factor α is shown in Figure 11. This graph depicts the behavior of SSIM values for various α values. Each line on the graph represents a different attack, such as a Gaussian low-pass filter, a Median, Salt and Pepper noise, Speckle noise, JPEG compression, sharpening attack, histogram equalization, an average filter, Gaussian noise, JPEG2000 compression, and motion graph of NC versus scaling factor α is shown in Figure 12. This graph depicts the behavior of NC values for various α values. Each line on the graph represents a different attack, such as a Gaussian low-pass filter, a median, salt and pepper noise, speckle noise, JPEG compression, sharpening attack, histogram equalization, an average filter, Gaussian noise, JPEG2000 compression, and motion blur. Figures 13a and 13b show a graph of PSNR versus different scaling factors α or β. This graph shows the behavior of PSNR values for different α or β values. A Gaussian low-pass filter, a Median, Salt and Pepper noise, Speckle noise, JPEG compression, sharpening attack, Histogram equalization, an Average filter, Gaussian noise, JPEG2000 compression, and Motion blur are all represented by lines on the graph. Figure 14 depicts graphs of NC values under various parameters subjected to various attacks. Each line in the graphs represents a different image size, such as 512 × 512, 256 × 256, and 128 × 128. The X-axis parameters are a quality factor, compression ratio, sigma, window size, variance, and strength 1- Threshold. The graph varies depending on the type of attack used.a b Table 1 shows Normalized Correlation NC values for biometric NCB and signature NCS under different types of attacks. The achieved results show better NC values for all the test cases even after the extraction of watermarks biometric and signature.Table 2 details the invisibility imperceptibility property of the watermark of the proposed watermarking scheme for different types of images. It clearly shows that the proposed algorithm for all seven images showcases an average PSNR value of and an average SSIM value of 3 depicts Peak Signal to Noise Ratio PSNR values for biometric PSNRB and signature PSNRS under different types of attacks. In the above-mentioned test cases, the results acquired are with good PSNR values even after the extraction of watermarks biometric and signature.Table 4 depicts Structural Similarity Index Metrics SSIM values for biometric SSIMB and signature SSIMS under different types of attacks. For all the above-mentioned test cases, the results achieved are with good SSIM values even after the extraction of watermarks viz, biometric, and 5 shows the NC values of various watermarked images host image where the two watermarks biometric and signature are embedded. The NC values are good enough to achieve the property of imperceptibility of both the watermarks. The table details that the proposed scheme shows comparatively good results on Lena image for crop, salt & pepper, and speckle attacks. The proposed scheme shows results on other attacks such as rotation and scaling attacks. For peppers image, the proposed scheme shows similar results to the related work [1]. It can be depicted from Table 5 that the proposed methodology DWT-DCT-SVD shows comparatively good results for all the 15 different types of attacks on Lena and Pepper ConclusionThis study extends a watermarking stratagem deployed on both transform DCT-DWT and spatial SVD domain methods. Watermarked image implementation has good PSNR, NC, and SSIM due to DCT’s energy compaction property and DWT has a better compression ratio. The results show that the proposed method besides being protective against attacks, and deployed method improves performance without sacrificing image information. The robustness of the projected watermarking strategy was assessed by performing attacks such as added noise, filtering attacks, geometrical attacks, and compression attacks. The deployed method was validated with regard to the imperceptibility of the watermarked image. The deployed method exhibits the experimental results which achieved an average PSNR of 40 dB value, an NC value of and an SSIM value of approximately In the future, more enhanced embedding techniques may be deployed to improve the standard of watermarked images meanwhile taking the flaws into account. In the future, this method can be improved by combining it with other watermarking techniques that are more conscientious and resistant to attack. The proposed method can embed a watermark into standard digital media such as audio, text, zip archives, and video, as well as holograms and 3D vector objects. This work can be expanded to conceal user data and personal AvailabilityThe dataset used for the findings can be obtained from the corresponding author upon reasonable of InterestThe authors declare that there are no conflicts of interest regarding the publication of this © 2022 Bhargavi Mokashi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Buat para pecinta fotografi pasti rasanya sangat senang sekali saat karya-karya kamu bisa dinikmati bukan hanya oleh diri sendiri saja tapi juga oleh banyak orang. Untungnya, saat ini kehadiran platform media sosial seperti Instagram bisa dimanfaatkan untuk membagikan karya-karya kamu itu, geng. Namun permasalahannya adalah, banyak orang nggak bertanggung jawab yang asal ambil dan mengakuinya sebagai karya mereka sendiri. Nah, untuk menghindari hal tersebut, kamu bisa lho menambahkan watermark pada hasil foto sehingga nggak sembarang orang bisa mengakuinya. Aplikasi Untuk Membuat Watermark Jika para profesional biasanya menambahkan watermark dengan menggunakan aplikasi-aplikasi yang cukup rumit digunakan oleh orang awam, saat ini ada banyak aplikasi Andorid yang menawarkan fasilitas ini, geng. Nah, berikut adalah beberapa rekomendasi aplikasi Android untuk menambahkan watermark pada foto, geng. 1. Add Watermark on Photos Add Watermark on Photos Apps DOWNLOAD Sesuai dengan namanya, Add Watermark on Photos adalah aplikasi yang memungkinkan pengguna untuk menambahkan watermark pada sebuah foto. 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Keterangan Photo Watermark Developer MVTrail Tech Ulasan Jumlah Pengulas Ukuran 15MB Instal 1M+ Android Minimum 3. Watermark Maker - Add Watermark to Photos Watermark Maker - Add Watermark to Photos Apps DOWNLOAD Menawarkan user interface UI yang sederahana namun tetap menarik, aplikasi Watermark Maker bisa membantu kamu terhindar dari penyalahgunaan foto secara ilegal, geng. Aplikasi Watermark Maker sendiri memiliki banyak sekali fitur yang bisa membantu kamu mempermudah proses pembuatan logo watermark. Beberapa fitur yang menjadi andalannya adalah menyimpan hasil rancangan sebagai template, pilihan font, warna, dan ukuran yang bergam, tanda tangan digital, dan masih banyak lagi. Keterangan Watermark Maker - Add Watermark to Photos Developer Cute Wallpapers Studio Ulasan Jumlah Pengulas 573 Ukuran 21MB Instal 50K+ Android Minimum 4. iWatermark Free Add Watermark Text Logo Pic TM iWatermark Free Add Watermark Text Logo Pic TM Apps DOWNLOAD Telah didownload oleh lebih dari 500 ribu pengguna, aplikasi iWatermark nggak hanya tersedia untuk HP Android saja tapi juga untuk perangkat iOS, Mac, dan Windows. Serupa dengan aplikasi watermark lainnya, iWatermark menyediakan beragam fitur menarik yang dapat memudahkan pengguna saat membuat watermark. Fitur-fitur yang disediakan oleh aplikasi ini sendiri meliputi pilihan font yang beragam, pengaturan transapransi, warna, rotasi, dan lainnya. Sayangnya, aplikasi iWatermark gratis ini akan menempelkan watermark 'Dibuat dengan iWatermark' pada hasil editan, geng. Keterangan iWatermark Free Add Watermark Text Logo Pic TM Developer Plum Amazing Ulasan Jumlah Pengulas Ukuran 10MB Instal 500K+ Android Minimum 5. Video Watermark - Crate & Add Watermark on Videos Video Watermark - Crate & Add Watermark on Videos Apps DOWNLOAD Jika aplikasi-aplikasi sebelumnya berfungsi untuk membuat watermark dalam sebuah foto, maka aplikasi Video Watermark ini berfungsi untuk membuat watermark pada video, geng. Nggak sesulit yang mungkin kamu bayangkan, aplikasi Video Watermark adalah aplikasi yang cepat dan mudah digunakan untuk membuat dan menerapkan watermark pada video. Aplikasi Video Watermark sendiri dibekali dengan fitur-fitur yang serupa dengan aplikasi-aplikasi sebelumnya. Keterangan Video Watermark Developer Z Mobile Apps Ulasan Jumlah Pengulas Ukuran 57MB Instal 500K+ Android Minimum 6. Add Watermark on Videos & Photos Add Watermark on Videos & Photos Apps DOWNLOAD Lagi cari aplikasi yang menawarkan fasilitas untuk menambahkan watermark pada foto dan video sekaligus dalam satu aplikasi? Kalau gitu aplikasi satu ini cocok buat kamu download, geng. Sesuai dengan namanya, aplikasi Add Watermark on Videos & Photos ini memungkinkan kamu untuk menambahkan watermark baik pada file foto ataupun video yang kamu punya, geng. Menariknya, aplikasi Add Watermark on Videos & Photos ini diklaim mampu mempertahankan kualitas resolusi file aslinya sehingga kualitas akan tetap terjamin. Keterangan Add Watermark on Videos & Photos Developer Z Mobile Apps Ulasan Jumlah Pengulas Ukuran 43MB Instal 100K+ Android Minimum 7. Dynamo - Watermark Video Animasi Dynamo - Watermark Video Animasi Apps DOWNLOAD Rekomendasi terakhir aplikasi untuk membuat watermark adalah Dynamo - Watermark Video Animasi, geng. Berbeda dengan aplikasi lainnya, Dynamo menawarkan watermark dalam bentuk animasi bergerak yang bisa kamu atur sendiri desain dan gerakannya. Namun sayangnya, hasil watermark yang dibuat di aplikasi ini hanya bisa ditambahkan ke file video saja, geng. Dengan aplikasi ini, kamu nggak perlu lagi deh install aplikasi edit video yang cara penggunaannya pun lebih ribet. Keterangan Dynamo - Watermark Video Animasi Developer photoshop mobile apps Ulasan Jumlah Pengulas Ukuran 43MB Instal 100K+ Android Minimum Akhir Kata Nah, itulah tadi beberapa aplikasi untuk membuat watermark yang bisa digunakan untuk melindungi hasil karya kamu, geng. Dengan begitu, karya kamu akan aman dari tangan-tangan jahil orang yang asal main comot karya orang. Baca juga artikel seputar Aplikasi Android atau artikel menarik lainnya dari Shelda Audita. ARTIKEL TERKAIT 10 Aplikasi Download Permainan Android Terbaik 2021 Koleksinya Lengkap! 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