0483329 20240103215204.320171218235959.9 85038026758 000424296400012 10.1016/j.forsciint.2017.11.031 11 s. P cav_un_epca*02566270379-07382831 (2018)47-57Elsevier Copy-move modification Forgery Image tampering Quantization constraint set cav_un_auth*0283562 Novozámský Adam Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0108377 Šorel Michal Zpracování obrazové informace Department of Image Processing ZOI ZOI UTIA-B Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2017/ZOI/novozamsky-0483329.pdf cav_un_auth*0338628 GA16-13830S GA ČR CZ cav_un_auth*0314467 GA15-16928S GA ČR The so-called copy-move forgery, based on copying an object and pasting in another location of the same image, is a common way to manipulate image content. In this paper, we address the problem of copy-move forgery detection in JPEG images. The main problem with JPEG compression is that the same pixels, after moving to a different position and storing in the JPEG format, have different values. The majority of existing algorithms is based on matching pairs of similar patches, which generates many false matches. In many cases they cannot be eliminated by postprocessing, causing the failure of detection. To overcome this problem, we derive a JPEG-based constraint that any pair of patches must satisfy to be considered a valid candidate and propose an efficient algorithm to verify the constraint. The constraint 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. JD 10000 10200 10201 2019 2 4 A hod 4ah 20231122142908.7 RVO:67985556 http://hdl.handle.net/11104/0278697 1 Department of Image Processing UTIA-B 10200 COMPUTER SCIENCE, THEORY & METHODS S 1 Article Medicine Legal MEDICINE.LEGAL 2.269 0.382 3.9 0.01356 0.513 13842 0.879 1.607 435 Q2 55.496 73.5 Q2 Q2 1.14 Q2 73.529 2018 Soubory v repozitáři: novozamsky-0483329.pdf 85038026758 SCOPUS PUBMED 000424296400012 WOS cav_un_epca*0256627 Forensic Science International 0379-0738 1872-6283 Roč. 283 č. 1 2018 47 57 Elsevier