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- W3163489090 abstract "As an active forensic technology, perceptual image hash has important application in image content authenticity detection and integrity authentication. In this paper, we propose a hybrid-feature-based perceptual image hash method that can be used for image tampering detection and tampering localization. In the proposed method, we use the color features of image as global features, use point-based features and block-based features as local features, and combine with the structural features to generate intermediate hash code. Then we encrypt and randomize to generate the final hash code. Using this hash code, we present a coarse-to-fine grained forensics method for image tampering detection. The proposed method can realize object-level tampering localization. Abundant experimental results show that the proposed method is sensitive to content changes caused by malicious attacks, and the tampering localization precision achieves pixel level, and it is robust to a wide range of geometric distortions and content-preserving manipulations. Compared with the state-of-the-art schemes, the proposed scheme yields superior performance." @default.
- W3163489090 created "2021-05-24" @default.
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- W3163489090 date "2021-07-01" @default.
- W3163489090 modified "2023-10-17" @default.
- W3163489090 title "Perceptual hash-based coarse-to-fine grained image tampering forensics method" @default.
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- W3163489090 doi "https://doi.org/10.1016/j.jvcir.2021.103124" @default.
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