Forgery Localization Based on Image Chroma Feature Extraction

Many passive image tamper detection techniques have been presented in the expanding field of image forensics. Some of these techniques use a classifier for a final decision based on whole image statistics, resulting in a lack of forgery localization. The aim of this paper is to add localization to a previously published algorithm that uses grey-level co-occurrence matrix (GLCM) for extracting texture features from the chromatic component of an image (Cb or Cr component). Experimental results show that we can localize tampering for different sized regions with reasonable accuracy. The main trade-off is a diminishing detection accuracy as the region size decreases.