A Remediable Image Authentication Scheme Based on Feature Extraction and Clustered VQ

Abstract

We present an image authentication scheme based on feature extraction and codeword clustering in this paper. The two-level detections can be performed progressively based on the requirements of the authenticator. In order to generate these two-level authentication codes, the quad-tree segmentation and clustered VQ techniques are used. Using the first-level authentication code, the malicious tampered areas can be detected and located. In the second-level, it not only provides a more rigid detection of tampered areas but also can further remedy them. According to the experimental results, our scheme can correctly detect the malicious tampering and tolerate some incidental modifications, and then successfully remedy the tampered area. In addition, the space cost of authentication code is quite little.