Abstract
This paper present a novel content-based image authentication framework which embeds the semi-fragile image feature into the host image based on wavelet transform. In this framework, two features of a target image from the low frequency domain to generate two watermarks: Zernike moments for classifying of the intentional content modification and sobel edge for indicating the modified location. In particular, we design a systematic method for automatic order selection of Zernike moments and in order to tell if the procession on the image is malicious or not, we also propose a weighted Euclidean distance by its reconstruction process. An important advantage of our approach is that it can tolerate compression and noise to a certain extent while rejecting common tampering to the image like rotation. Experimental results show that the framework can locate the malicious tamper locally, the unit of detection region is 8x8 block, while highly robust to content preserved processing, such as JPEG compression Q>=30 and Gaussian noise variance<=20.