Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining

arXiv:2404.00611v1 Announce Type: new
Abstract: In copy-move tampering operations, perpetrators often employ techniques, such as blurring, to conceal tampering traces, posing significant challenges to the detection of object-level targets with intact structures. Focus on these challenges, this paper proposes an Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining (IMNet). To obtain complete object-level targets, we customize prototypes for both the source and tampered regions and dynamically update them. Additionally, we extract inconsistent regions between coarse similar regions obtained through …

abstract arxiv challenges copy cs.cv detection focus forgery image image detection mining object operations paper targets traces type