Segmentation-Based Image Copy-Move Forgery Detection Scheme

doi:10.1109/TIFS.2014.2381872

CORC > 北京大学 > 信息科学技术学院

	Segmentation-Based Image Copy-Move Forgery Detection Scheme
	Li, Jian ; Li, Xiaolong ; Yang, Bin ; Sun, Xingming
刊名	ieee transactions on information forensics and security
	2015
关键词	Copy-move forgery detection image forensics segmentation ENERGY MANAGEMENT FEATURES SHAPES
DOI	10.1109/TIFS.2014.2381872
英文摘要	In this paper, we propose a scheme to detect the copy-move forgery in an image, mainly by extracting the keypoints for comparison. The main difference to the traditional methods is that the proposed scheme first segments the test image into semantically independent patches prior to keypoint extraction. As a result, the copy-move regions can be detected by matching between these patches. The matching process consists of two stages. In the first stage, we find the suspicious pairs of patches that may contain copy-move forgery regions, and we roughly estimate an affine transform matrix. In the second stage, an Expectation-Maximization-based algorithm is designed to refine the estimated matrix and to confirm the existence of copy-move forgery. Experimental results prove the good performance of the proposed scheme via comparing it with the state-of-the-art schemes on the public databases.; Computer Science, Theory & Methods; Engineering, Electrical & Electronic; SCI(E); EI; 2; ARTICLE; ljian20@gmail.com; lixiaolong@pku.edu.cn; yang_bin@pku.edu.cn; sunnudt@163.com; 3; 507-518; 10
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/206338]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Jian,Li, Xiaolong,Yang, Bin,et al. Segmentation-Based Image Copy-Move Forgery Detection Scheme[J]. ieee transactions on information forensics and security,2015.
APA	Li, Jian,Li, Xiaolong,Yang, Bin,&Sun, Xingming.(2015).Segmentation-Based Image Copy-Move Forgery Detection Scheme.ieee transactions on information forensics and security.
MLA	Li, Jian,et al."Segmentation-Based Image Copy-Move Forgery Detection Scheme".ieee transactions on information forensics and security (2015).