An improved video watermarking algorithm with extraction using a mobile device camera

An improved video watermarking algorithm with extraction using a mobile device camera

Автор: Evsutin O.O., Melman A.S., Podbolotov D.I., Stankevich A.G.

Журнал: Компьютерная оптика @computer-optics

Рубрика: Обработка изображений, распознавание образов

Статья в выпуске: 6 т.47, 2023 года.

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The use of screen-capture-resistant digital watermarks is a promising way to store information invisibly in a video stream for later retrieval by the user using a smartphone camera. However, the development of algorithms that implement this scenario is associated with the problem of balancing between the imperceptibility of embedding and robustness. A serious problem is the extraction of watermarks using a mobile device. Most people use the vertical positioning of the smartphone when shooting, which excludes the possibility of only marked video sequences entering the frame. The extraction algorithm first finds the screen area in the image and then extracts the watermark under various distortion conditions. This study proposes an approach to improve the efficiency of the algorithm for embedding digital watermarks into video data based on rectangular patterns, which provides resistance to screen shooting. The proposed approach to increasing the embedding imperceptibility provided an increase in the PSNR and SSIM values by 17.18 % and 7.90 %, respectively. The use of a neural network at the extraction stage reduced the BER value by 64.64 %.

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Digital watermark, video, neural network, screen capture

Короткий адрес: https://sciup.org/140303286

IDR: 140303286   |   DOI: 10.18287/2412-6179-CO-1328

Список литературы An improved video watermarking algorithm with extraction using a mobile device camera

  • Egorova AA, Fedoseev VA. A classification of semifragile watermarking systems for JPEG images. Computer Optics 2019; 43(3): 419-433. DOI: 10.18287/2412-61792019-43-3-419-433.
  • Vybornova YD, Sergeev VV. A new watermarking method for vector map data. Computer Optics 2017; 41(6): 913-919. DOI: 10.18287/2412-6179-2017-41-6-913-919.
  • Melman A, Evsutin O, Shelupanov A. An authorship protection technology for electronic documents based on image watermarking. Technologies 2020; 8(4): 79. DOI: 10.3390/technologies8040079.
  • Mitekin VA. An algorithm for generating digital watermarks robust against brute-force attacks. Computer Optics 2015; 39(5): 808-817. DOI: 10.18287/0134-24522015-39-5-808-817.
  • Choi Y-H, Kim D, Rho S, Hwang E. Converting image to a gateway to an information portal for digital signage. Multimed Tools Appl 2014; 71(1): 263-278. DOI: 10.1007/s11042-012-1315-6.
  • Chen Y-Y, Chi K-Y, Hua K-L. Design of image barcodes for future mobile advertising. EURASIP J Image Video Process 2017; 2017: 11. DOI: 10.1186/s13640-016-0158-x.
  • Iwata M, Mizushima N, Kise K. Practical watermarking method estimating watermarked region from recaptured videos on smartphone. IEICE Trans Inf Syst 2017; E100.D(1): 24-32. DOI: 10.1587/transinf.2016MUP0008.
  • Sridhar B, Syambabu V. Security enhancement in video based on gatefold technique for copyright protection. Multimed Tools Appl 2021; 80(14): 8241-8256. DOI: 10.1007/s11042-020-09909-z.
  • Pandey MK, Parmar G, Gupta R, Sikander A. Non-blind Arnold scrambled hybrid image watermarking in YCbCr color space. Microsyst Technol 2019; 25(8): 3071-3081. DOI: 10.1007/s00542-018-4162-1.
  • Priya C, Ramya C. Robust and secure video watermarking based on cellular automata and singular value decomposition for copyright protection. Circuits Syst Signal Process 2021; 40(5): 2464-2493. DOI: 10.1007/s00034-020-01585-6.
  • Gong L-H, Tian C, Zou W-P, Zhou N-R. Robust and imperceptible watermarking scheme based on Canny edge detection and SVD in the contourlet domain. Multimed Tools Appl 2021; 80(1): 439-461. DOI: 10.1007/s11042-020-09677-w.
  • Kang X, Chen Y, Zhao F, Lin G. Multi-dimensional particle swarm optimization for robust blind image watermarking using intertwining logistic map and hybrid domain. Soft Comput 2020; 24(12): 10561-10584. DOI: 10.1007/s00500-019-04563-6.
  • Cedillo-Hernandez M, Cedillo-Hernandez A, Garcia-Ugalde FJ. Improving DFT-based image watermarking using particle swarm optimization algorithm. Mathematics 2021; 9(15): 1795. DOI: 10.3390/math9151795.
  • Singh P, Devi KJ, Thakkar HK, Santamaría J. Blind and secured adaptive digital image watermarking approach for high imperceptibility and robustness. Entropy 2021; 23(12): 1650. DOI: 10.3390/e23121650.
  • Zhong X, Huang P-C, Mastorakis S, Shih FY. An automated and robust image watermarking scheme based on deep neural networks. IEEE Trans Multimedia 2021; 23: 1951-1961. DOI: 10.1109/TMM.2020.3006415.
  • Zhu L, Wen X, Mo L, Ma J, Wang D. Robust location-secured high-definition image watermarking based on keypoint detection and deep learning. Optik 2021; 248: 168194. DOI: 10.1016/j.ijleo.2021.168194.
  • Sinhal R, Jain DK, Ansari IA. Machine learning based blind color image watermarking scheme for copyright protection. Pattern Recogn Lett 2021; 145: 171-177. DOI: 10.1016/j.patrec.2021.02.011.
  • Chen W, Zhu C, Ren N, Seppanen T, Keskinarkaus A. Screen-cam robust and blind watermarking for tile satellite images. IEEE Access 2020; 8: 125274-125294. DOI: 10.1109/ACCESS.2020.3007689.
  • Fang H, Zhang W, Zhou H, Cui H, Yu N. Screen-shooting resilient watermarking. IEEE Trans Inf Forensics Secur 2019; 14(6): 1403-1418. DOI: 10.1109/TIFS.2018.2878541.
  • Pramila A, Keskinarkaus A, Takala V, Seppanen T. Extracting watermarks from printouts captured with wide angles using computational photography. Multimed Tools Appl 2017; 76(15): 16063-16084. DOI: 10.1007/s11042-016-3895-z.
  • Huang K, Tian X, Yu H, Yu M, Yin A. A high capacity watermarking technique for the printed document. Electronics 2019; 8(12): 1403. DOI: 10.3390/electronics8121403.
  • Choi D, Do H, Choi H, Kim T. A blind MPEG-2 video watermarking robust to camcorder recording. Signal Process 2010; 90(4): 1327-1332. DOI: 10.1016/j.sigpro.2009.10.009.
  • Li L, Dong Z, Lu J, et al. AN H.264/AVC HDTV watermarking algorithm robust to camcorder recording. J Vis Commun Image Represent 2015; 26: 1-8. DOI: 10.1016/j.jvcir.2014.08.009.
  • Gaj S, Rathore AK, Sur A, Bora PK. A robust watermarking scheme against frame blending and projection attacks. Multimed Tools Appl 2017; 76(20): 20755-20779. DOI: 10.1007/s11042-016-3961-6.
  • Dubey N, Modi H. A robust discrete wavelet transform based adaptive watermarking scheme in YCbCr color space against camcorder recording in Cinema/Movie Theatres. Eng Sci 2021; 15: 116-128. DOI: 10.30919/es8d491.
  • Asikuzzaman Md, Mareen H, Moustafa N, Choo K-KR, Pickering MR. Blind camcording-resistant video watermarking in the DTCWT and SVD domain. IEEE Access 2022; 10: 15681-15698. DOI: 10.1109/ACCESS.2022.3146723.
  • Dorad. Image Color Analysis Tool. MATLAB Central File Exchange. 2022. Source: https://www. mathworks.com/matlabcentral/fileexchange/ 75116-image-color-analysis-tool.
  • Kalinina MO, Nikolaev PL. Book spine recognition with the use of deep neural networks. Computer Optics 2020; 44(6): 968-977. DOI: 10.18287/2412-6179-C0-731.
  • Makarkin M, Bratashov D. State-of-the-art approaches for image deconvolution problems, including modern deep learning architectures. Micromachines (Basel) 2021; 12(12): 1558. DOI: 10.3390/mi12121558.
  • Ronneberger O, Fischer P, Brox T. U-Net: Convolutional networks for biomedical image segmentation. In Book: Navab N, Hornegger J, Wells WM, Frangi AF, eds. Medical image computing and computer-assisted intervention - MICCAI 2015. Cham: Springer International Publishing; 2015: 234-241. DOI: 10.1007/978-3-319-24574-4_28.
  • Video tools. Online [In Russian]. Source: https://clideo.com/.
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