Image authentication based on perceptual hash using Gabor filters

Image authentication is an important topic in image forensics, which tells whether an image is tampered or not or even tells the tampered regions. To implement image authentication, image hash techniques have been reported recently. In this paper, we investigate existing image hash algorithms, and design an novel image hash based on human being's visual system. In this algorithm, we capture the perceptual characters of the image using Gabor filter which can sense the directions in the image just like human’s primary visual cortex. For a given image, we compute the reference scale, direction and block to make sure the final hash can resist against rotation, scale, and translation attacks while maintain the sensitivity to local malicious manipulations. In addition, it has another promising ability to locate the tampered image blocks, and approximately determining the type of tampering methods (delete, add, modify) and the original direction of each block. This ability is very useful in forensics. The experimental results show that the strategy of the reference metrics works quite well and our method is much more effective than the other state of art image hash methods. Moreover, our method can still locate the content-altering changes even undergo some content-preserving manipulations.