Image Authenticity Detection Using DWT and Circular Block-Based LTrP Features

Copy-move forgery is the most common type of digital image manipulation, in which content from same used to forge it. Such manipulations are performed hide desired information. Therefore, detection methods required identify forged areas. We have introduced a novel method for features computation by employing circular block-based through local tetra pattern (LTrP) detect single and multiple copy-move attacks images. The proposed applied over blocks efficiently effectively deal with post-processing operations. It also uses discrete wavelet transform (DWT) dimension reduction. obtained approximate distributed into on LTrP algorithm employed calculate feature vector as provides detailed information about utilizing direction-based relation central pixel its neighborhoods. Finally, Jeffreys Matusita distance similarity measurement. For evaluation results, three datasets used, namely MICC-F220, MICC-F2000, CoMoFoD. Both qualitative quantitative analysis shows that exhibits state-of-the-art performance under presence operations can accurately locate