This paper presents a novel hybrid copy–move forgery detection method that combines the efficiency of FAST-BRIEF (for rapid keypoint detection and binary descriptors) with the robustness of SIFT (for scale- and rotation-invariant feature matching). The proposed framework employs g2NN matching for accurate feature correspondence, followed by morphological processing and LSC-SSIM superpixel segmentation for precise localization of tampered regions. The method is evaluated on 30 diverse test images from benchmark datasets comprising over 700 images, achieving a 95% F-measure with an average CPU time of 6.02 seconds. It demonstrates strong resilience to geometric transformations (rotation, sca... More >