0482763 20240111140952.820171207235959.9 85050670586 000428743900063 10.1109/IPTA.2017.8310139 6 s. C cav_un_epca*0482762978-1-5386-1843-1MontrealIEEE2017 Image forensics Copy-move forgery detection Image tampering JPEG Quantization constraint set cav_un_auth*0283562 50 Novozámský Adam UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0108377 50 Šorel Michal UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. pdf http://library.utia.cas.cz/separaty/2017/ZOI/novozamsky-0482763.pdf cav_un_auth*0338628 GA16-13830S GA ČR CZ cav_un_auth*0314467 GA15-16928S GA ČR CZ The integrity of visual data is important for the credibility of news media and especially when used as an evidence in court or during criminal investigation. The common way to manipulate image content is copying an object and pasting in another location of the same image. In this paper, we describe a new idea for the detection of this type of forgery in JPEG images, where the compression significantly degrades detection by popular algorithms. We derive a JPEG-based constraint that any pair of patches must satisfy to be considered a valid candidate for tampered area. We propose also efficient algorithm to verify the constraint that can be integrated into most existing methods. Experiments show significant improvement of detection, especially for difficult cases, such as small objects, objects covered by textureless areas and repeated patterns. cav_un_auth*0354801 International Conference on Image Processing Theory, Tools and Applications (IPTA 2017) /7./ 20171128 20171201 Montreal CA JD 20000 20200 20205 2018 2 PR RVO:67985556 http://hdl.handle.net/11104/0278140 1 S 65 RIV/67985556:_____/17:00482763!RIV18-AV0-67985556 191975728 Doplnění UT WOS a Scopus RIV/67985556:_____/17:00482763!RIV18-GA0-67985556 191965056 Doplnění UT WOS a Scopus 3+4 Proceedings Paper Computer Science Artificial Intelligence|Engineering Electrical Electronic|Imaging Science Photographic Technology 3+4 Proceedings Paper Computer Science Artificial Intelligence|Engineering Electrical Electronic|Imaging Science Photographic Technology 3+4 Proceedings Paper Computer Science Artificial Intelligence|Engineering Electrical Electronic|Imaging Science Photographic Technology 2017 85050670586 SCOPUS PUBMED 000428743900063 WOS pdf cav_un_epca*0482762 Proceedings of the Seventh International Conference on Image Processing Theory, Tools and Applications 978-1-5386-1843-1 Montreal IEEE 2017