A Novel Image Tamper Detection and Self-Recovery Algorithm Based on Watermarking and Chaotic System

Abstract

With the development of image editing software techniques, the content integrity and authenticity of original digital images become more and more important in digital content security. A novel image tampering detection and recovery algorithm based on digital watermarking technology and a chaotic system is proposed, and it can effectively locate the tampering region and achieve the approximate recovery of the original image by using the hidden information. The pseudo-random cyclic chain is realized by the chaotic system to construct the mapping relationship between the image subblocks. It can effectively guarantee the randomness of the positional relationship between the hidden information and the original image block for the better ergodicity of the pseudo-random chain. The recovery value optimization algorithm can represent image information better. In addition to the traditional Level-1 recovery, a weight adaptive algorithm is designed to distinguish the original block from the primary recovery block, allowing 3 × 3 neighbor block recovery to achieve better results. The experimental results show that the hierarchical tamper detection algorithm makes tamper detection have higher precision. When facing collage attacks and large general tampering, it will have higher recovery image quality and better resistance performance.

Cost assignment based adaptive active forensics scheme for image tampers

“…Experimental results in Table 4 show that the schemes in Refs. 24, 39, 40 and 41 provide lower PSNR values and SSIM values than that in schemes Refs. 17, 42, and 43 and the proposed scheme.…”

“…Also, compared with schemes in Refs. 39–41, the embedding modifications are smaller. Therefore, the better image quality is achieved.…”

“…To further explain our performance clearly, we choose Refs. 17, 24, and 39–43 as references. The results are found in Table 4, which shows the proposed scheme with better image quality in our experiments.…”

“…For schemes in Refs. 39–41, the lower image quality caused by big embedding modifications, e.g., in Ref. 39, one bit is embedded by modifying spatial pixel with range ±8.…”

“…As shown in Fig. 15, Gull scheme, 43 Li scheme, 39 Haghighi scheme, 40 and Aminuddin scheme 24 are as implemented as reference schemes. We can see that the proposed scheme provides a higher robustness for resisting the noise attack.…”