Image Tamper Detection and Recovery based on Dilation and Chaotic Mixing

Abstract

In this paper, we propose an efficient method for image tamper detection and recovery. We separate the image into several blocks, and share a block information to two other blocks. It means, there have two copies of one block information for each non-overlapping block. In implementing, we improve Lee's algorithm of watermark embedding, especially when the tampered area is a rounded region or a text field, and our scheme has higher PSNR value than Lee's method. During image recovery, we use the image inpainting approach to fill the tampered region of whole image. The experimental result shows that our scheme is effective than Lee's interpolation method.