Structural Feature-Based Image Hashing and Similarity Metric for Tampering Detection

• Autorzy: Tang Z. , Wang S. , Zhang X. , Wei W.
• Języki publikacji: EN

Abstrakty

EN

Structural image features are exploited to construct perceptual image hashes in this work. The image is first preprocessed and divided into overlapped blocks. Correlation between each image block and a reference pattern is calculated. The intermediate hash is obtained from the correlation coefficients. These coefficients are finally mapped to the interval [0, 100], and scrambled to generate the hash sequence. A key component of the hashingmethod is a specially defined similarity metric to measure the "distance" between hashes. This similarity metric is sensitive to visually unacceptable alterations in small regions of the image, enabling the detection of small area tampering in the image. The hash is robust against content-preserving processing such as JPEG compression, moderate noise contamination, watermark embedding, re-scaling, brightness and contrast adjustment, and low-pass filtering. It has very low collision probability. Experiments are conducted to show performance of the proposed method.

Słowa kluczowe

EN

image hashing; tampering detection; content-based image retrieval (CBIR); structural feature; similarity metric; watermarking

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2011
• Tom: Vol. 106, nr 1
• Strony: 75--91
• Opis fizyczny: Bibliogr. 19 poz., fot., tab., wykr.

Twórcy

autor

Tang Z.

autor

Wang S.

autor

Zhang X.

autor

Wei W.

• School of Communication and Information Engineering, Shanghai University, 149 Yanchang Road, Shanghai 200072, China.,

Bibliografia

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