Perpetual Image Hashing Based on Conformal Mapping and Zernike Moments

We propose a perpetual image hashing method applicable to image authentication and tamper detection.The input image is pseudo-randomly partitioned into blocks,which are resized to become squares of a standard size and mapped to a unit circle by conformal mapping.Zernike moments of the circular-shaped "images" are calculated,and then modified by multiplying an exponent to achieve phase rotation-invariance. All amplitudes and phases of the modified Zernike moments are concatenated to form an intermediate Hash sequence.The final Hash is produced by pseudo-randomly permuting the intermediate Hash.The purpose of conformal mapping is to include information contained in the corners of square image blocks into the extracted image Hash so that the tamper detection capability is significantly enhanced.Experimental results show that the proposed method is robust against most content-preserving image processing operations.Image blocking allows the tampered regions in the image to be correctly located.Compared to some other techniques,the method has low probabilities of collision and less error in tamper detection.