Robustness of copy-move forgery detection under high JPEG compression artifacts
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- 作者：Deng-Yuan Huang ; Ching-Ning Huang ; Wu-Chih Hu…
- 关键词：Image forgery detection ; Principal component analysis ; Singular value decomposition ; Fast Fourier transform
- 刊名：Multimedia Tools and Applications
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：76
- 期：1
- 页码：1509-1530
- 全文大小：
- 刊物类别：Computer Science
- 刊物主题：Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems;
- 出版者：Springer US
- ISSN：1573-7721
- 卷排序：76
文摘
This paper proposes a robust method for detecting copy-move forgery in images under various JPEG compression and Gaussian noise and blurring attacks. The method comprises feature extraction, feature matching, and duplicate block identification. The fast Fourier transform (FFT), singular value decomposition (SVD), and principal component analysis (PCA) are utilized for feature extraction. Then, the cascading matchers of FFT, SVD, and PCA are adopted for feature matching. Matched blocks are identified using cascade filtering with city block, horizontal, vertical, and frequency filters. Finally, the pixels on upper left corners of detected duplicate blocks are output for visual inspection. The major contributions of this paper are: (1) the proposed method is fully threshold-free; (2) only one-dimensional features are generated using FFT and SVD for feature matching; and (3) a high accuracy rate (> 97 %) is obtained even if the JPEG quality factor Q is 20. In extensive experiments, a 98 % accuracy rate and a 6 % false negative rate were obtained for the worst case of Q = 20 and a region size of 32 × 32 pixels compared to existing works, indicating the feasibility of the proposed method.