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Image forensics has become increasingly important in our daily lives. As afundamental type of forgeries, Copy-Move Forgery Detection (CMFD) has receivedsignificant attention in the academic community. Keypoint-based algorithms,particularly those based on SIFT, have achieved good results in CMFD. However,the most of keypoint detection algorithms often fail to generate sufficientmatches when tampered patches are present in smooth areas. To tackle thisproblem, we introduce entropy images to determine the coordinates and scales ofkeypoints, resulting significantly increasing the number of keypoints.Furthermore, we develop an entropy level clustering algorithm to avoidincreased matching complexity caused by non-ideal distribution of grayscalevalues in keypoints. Experimental results demonstrate that our algorithmachieves a good balance between performance and time efficiency.

An effective image copy-move forgery detection using entropy image