A Secure Perceptual Hash Algorithm for Image Content Authentication

Perceptual hashing is a promising solution to image content authentication. However, conventional image hash algorithms only offer a limited authentication level for the protection of overall content. In this work, we propose an image hash algorithm with block level content protection. It extracts features from DFT coefficients of image blocks. Experiments show that the hash has strong robustness against JPEG compression, scaling, additive white Gaussian noise, and Gaussian smoothing. The hash value is compact, and highly dependent on a key. It has very efficient trade-offs between the false positive rate and the true positive rate.