Image Forgery Detection Based on Quantization Table Estimation

In this paper, we proposed a passive scheme to achieve image forgery. The inconsistent measure of quantization table is characterized to develop the proposed scheme. The proposed scheme is composed of candidate region selection, quantization table estimation, and forgery detection. To select candidate regions for estimating quantization table, a split-and-merge algorithm based on quad-tree decomposition is devised. To estimate the quantization table, we classify the type of PSD and then adjust the estimation algorithm. After quantization table estimation, the variation resulting from the inconsistent of quantization table is utilized to detect tampered regions. The experimental results show that our proposed scheme can not only estimates quantization table correctly but also detect tampered regions well.