期刊
MULTIMEDIA TOOLS AND APPLICATIONS
卷 76, 期 1, 页码 1509-1530出版社
SPRINGER
DOI: 10.1007/s11042-015-3152-x
关键词
Image forgery detection; Principal component analysis; Singular value decomposition; Fast Fourier transform
类别
资金
- Ministry of Science and Technology, Taiwan [NSC 102-2221-E-212-015, MOST 104-2221-E-212-005, MOST 104-2218-E-212-001]
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 x 32 pixels compared to existing works, indicating the feasibility of the proposed method.
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