Authentication of digital images and video: Generic models and a new contribution |
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| Affiliation: | 1. School of Cyber Engineering, Xidian University, Xi’an 710071, China;2. Shaanxi Key Laboratory of Network and System Security, Xidian University, Xi’an 710071, China;3. School of Telecommunication Engineering, Xidian University, Xi’an 710071, China;4. School of Computer Science and Technology, Xidian University, Xi’an 710071, China;5. School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710062, China;6. Chongqing Key Laboratory of Image cognition, Chongqing University of Posts and Telecommunications, 400065, China;7. School of Mathematics and Physics, Weinan Normal University, Weinan 714000, China;1. Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China;2. Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China;1. Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou 450000, Henan, China;2. Department of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou 450000, Henan, China;3. Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou 450000, Henan, China;4. International Joint Research Laboratory for Cell and Gene Therapy of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, 1 Jian-she East Road, Zhengzhou 450000, Henan, China;5. Institute of Clinical Medicine, The First Affiliated Hospital of Zhengzhou University, China |
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| Abstract: | This paper is focused on digital image and video authentication, considered as the process of evaluating the integrity of image contents relative to the original picture and of being able to detect, in an automatic way, malevolent content modifications. Generic models, corresponding to current approaches for content integrity evaluation – labeling and watermarking – are described, providing a common basis to compare existing techniques. Two labeling implementations are put forward. The first one is based on second-order image moments. It can be thought of as a low-level approach, where the emphasis is put on computational simplicity. The second one relies on image edges and tackles the problem of image/video integrity evaluation from a semantic, higher-level point of view. The viability of both methods, as a means of protecting the content, is assessed under JPEG and MPEG2 compression and non-authorized image modifications. |
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