Abstract:

As the classical correlation-based image tampering detection algorithms cannot avoid false alarm and misdetection,a novel algorithm based on double detection mechanisms is proposed. In this algorithm,first,tampered image blocks under suspicion are picked out according to the correlation between the camera fingerprint in each region of the detected image and that for reference. Then,image features are extracted from each suspicious image block and are sent to a trained SVM ( Support Vector Machine) to construct an image features-based SVM classifier for distinguishing the mis-detected blocks from the real tampered ones. Experimental results demonstrate that the proposed method outperforms the classical one only based on the correlation of camera fingerprints.

Key words: camera fingerprint, correlation detection, pattern classification, tampering detection, double detection mechanism