Image Copy-Move Forgery Detection using Color Features and Hierarchical Feature Point Matching

Abstract

In this study, an image copy-move forgery detection approach using color features and hierarchical feature point matching is proposed. The proposed approach contains three main stages, namely, pre-processing and feature extraction, hierarchical feature point matching, and iterative forgery localization and post-processing. In the proposed approach, Gaussian-blurred images and difference of Gaussians (DoG) images are constructed Hierarchical feature point matching is employed to find matched feature point pairs, in which two matching strategies, namely, group matching via scale clustering and group matching via overlapped gray level clustering, are used. Based on the experimental results obtained in this study, the performance of the proposed approach is better than those of three comparison approaches.