Gauss–Jordan elimination-based image tampering detection and self-recovery

Abstract

This paper proposes a novel Gauss–Jordan elimination-based image tampering detection and self-recovery scheme, aiming at dealing with the problem of malicious tampering on digital images. To deal with the copy–move tampering which is challenging because the tampered region may contain the watermark information, we propose the Improved Check Bits Generation algorithm during watermark generation, to generate the check bits for tampering detection. Meanwhile, the recovery bits are reconstructed according to the fundamental of Gauss–Jordan Elimination, for purpose of image contents self-recovery. To improve the accuracy of detection and the quality of recovered images, we propose the Morphological Processing-Based Enhancement method and the Edge Extension preprocessing respectively during and after the tampering detection Finally, the Gauss–JordanElimination-Based Self-Recovery method is proposed to recover the damaged content mathematically on basis of the detected results. By employing the unchanged recovery bits which are embedded in the non-tampered region, the failure in recovery caused by the damaged recovery bits can be completely avoided. A large number of experiments have been conducted to show the very good performance of the proposed scheme. The precision, recall, and F1 score are calculated for evaluation of tampering detection, while the PSNR values are calculated for evaluation of image recovery. The comparisons with the state-of-the-art methods show that the proposed scheme shows the superiorities in terms of imperceptibility, security and recovery capability. The experimental result indicates the average PSNR of recovered image is 44.415dB.