Abstract
Tampered image discovery from similar images is a challenging problem of multimedia security. Aiming at this issue, we propose a robust image hashing with invariant moments. Specifically, the proposed hashing firstly converts the input image into a normalized image by interpolation, filtering and color space conversion. Then it divides the normalized image into overlapping blocks and extracts invariant moments of blocks to form a feature matrix. Finally, the feature matrix is compressed to make a short hash. Hash similarity is determined by measuring similarity between hash segments with correlation coefficient. Experimental results indicate that our hashing is robust against normal digital operations and can efficiently distinguish tampered images from similar images. Comparisons show that our hashing is better than some notable hashing algorithms in classification performances between robustness and content sensitivity.
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Tang, Z., Yu, J., Zhang, X., Zhang, S. (2014). Discovery of Tampered Image with Robust Hashing. In: Luo, X., Yu, J.X., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2014. Lecture Notes in Computer Science(), vol 8933. Springer, Cham. https://doi.org/10.1007/978-3-319-14717-8_9
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DOI: https://doi.org/10.1007/978-3-319-14717-8_9
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