this paper, a shape feature using Zernike moments for image hash is proposed. At first the image is pre-processed and the color space of processed image is transformed from RGB to YCbCr. Then these three components are mapped to a unit circle. Zernike moments of three image components are calculated and the amplitudes and phases of modified Zernike moments are connected to form the intermediate hash. At last, the final hash sequence is obtained by pseudo-randomly permuting the intermediate hash sequence. Similarity between hashes is measured by a new distance defined in this paper. Experimental results show that this method is robust against most content-preserving attacks. The threshold used in image authentication can be got by robustness and uniqueness tests. And this method can be used to detect image forgery involving structural and color modifications.