High-Precision Authentication Scheme Based on Matrix Encoding for AMBTC-Compressed Images

Abstract

In this paper, a high-precision image authentication scheme for absolute moment block truncation coding (AMBTC)-compressed images is presented. For each block, two sub-bitmaps are conducted using the symmetrical separation, and the six-bit authentication code is symmetrically assigned to two sub-codes, which is virtually embedded into sub-bitmaps using the matrix encoding later. To overcome distortion caused by modifications to the bitmap, the corresponding to-be-flipped bit-location information is recorded instead of flipping these bits of the bitmap directly. Then, the bit-location information is inserted into quantization levels based on adjusted quantization level matching. In contrast to previous studies, the proposed scheme offers a significantly improved tampering detection ability, especially in the first hierarchical tampering detection without remediation measures, with an average tampering detection rate of up to 98.55%. Experimental results show that our approach provides a more stable and reliable tampering detection performance and sustains an acceptable visual quality.

Effective Self-Recovery and Tampering Localization Fragile Watermarking for Medical Images

“…Second, the performance of different kinds of attacks was analyzed. The latter part of this section compares our scheme with five existing block-based fragile watermarking schemes [17][18][19][20]25].…”

“…In Shehab et al's scheme [25], the watermark consists of a 12-bit authentication code and 20-bit recovery information, which is embedded into the 2LSBs of all pixels for a host image. The average PSNR of a watermarked image is about 44 dB.…”

“…1) PSNR [37]: Generally, PSNR is used to evaluate the distance between the recovered image and the original image. It is defined by: 2) Normalized cross-correlation (NCC) [25]: NCC is used to measure the similarity between two binary images. It is defined by:…”

“…However, they cannot localize the tampered area of an attacked image. Meanwhile, fragile watermarking-based methods [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][38][39][40][41] have been put forth for image authentication, image tampering localization and recovery. Generally, fragile watermarking first generates a watermark by exploiting an image feature.…”

“…In 2018, Shehab et al [25] proposed a singular value decomposition (SVD) based fragile watermarking scheme, which also achieves tampering localization and self-recovery. In their scheme, the watermark consisted of a 12-bit authentication code and 20-bit self-recovery information (SRI) for each 4  4 pixels block.…”