We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Robust copy-move forgery detection based on multi-granularity Superpixels matching.
- Authors
Yang, Hong-ying; Niu, Ying; Jiao, Li-xian; Liu, Yu-nan; Wang, Xiang-yang; Zhou, Zhi-li
- Abstract
In this paper, we propose a new multi-granularity superpixels matching based algorithm for the accurate detection and localization of copy-move forgeries, which integrated the advantages of keypoint-based and block-based forgery detection approaches. Firstly, we divide the original tempted image into non-overlapping and irregular coarse-granularity superpixels, and the stable image keypoints are extracted from each coarse-granularity superpixel. Secondly, the superpixel features, which is quaternion exponent moments magnitudes, are extracted from each coarse-granularity superpixel, and we find the matching coarse-granularity superpixels (suspected forgery region pairs) rapidly using the Exact Euclidean Locality Sensitive Hashing (E2LSH). Thirdly, the suspected forgery region pairs are further segmented into fine-granularity superpixels, and the matching keypoints within the suspected forgery region pairs are replaced with the fine-granularity superpixels. Finally, the neighboring fine-granularity superpixels are merged, and we obtain the detected forgery regions through morphological operation. Compared with the state-of-the-art approaches, extensive experimental results, conducted on the public databases available online, demonstrate the good performance of our proposed algorithm even under a variety of challenging conditions.
- Subjects
FORGERY prevention; FEATURE extraction; DIGITAL image processing; PIXELS; COMPUTER algorithms; STATISTICAL matching; HASHING
- Publication
Multimedia Tools & Applications, 2018, Vol 77, Issue 11, p13615
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-017-4978-1