Robust image hashing using invariants of Tchebichef moments

The content authenticity is critical for secure transmission of multimedia information. As a promising solution, perceptual image hashing has gain great attention. In this paper, we develop a novel algorithm for generating an image hash based on invariants of radial Tchebichef moments. The idea is justified by the fact that the radial Tchebichef moments represent the image under the orthogonal kernel, which has the desirable qualities of orthogonality and robustness. The hash values are achieved by adaptive quantization of the invariants of radial Tchebichef moments, then the random Gay code is applied in the discrete–binary conversion stage to enhance the expected discriminability. Experiments are conducted to show that the proposed hashing algorithm has superior robustness and discrimination performance compared with other state-of-the-art algorithms, in terms of receiving operating characteristic (ROC) curves.