In order to overcome the problem of false detection and missing detection when the threshold is not set properly, an image copy-paste tamper detection algorithm based on the optimal correlation rule of circle segmentation coupling is designed by using Cross-Correlation Function(CCF). The FAST operator is introduced to extract the image feature points accurately by calculating the gray value of the pixels and their adjacent points. Using the histogram information corresponding to the feature points, the principal direction of the feature points is obtained, and the neighborhood circle of the feature points is established in this direction. Through the segmentation of the circle, the gradient features of each segmentation area are obtained, and the feature vectors of the feature points are obtained. The correlation degree between feature points is calculated by CCF to construct the optimal correlation rule to complete feature matching. The Euclidean distance between feature points is calculated by matching the feature vectors of feature points. The feature points are clustered, and the copy-paste tampering content is locked to realize forgery detection. The simulation experiments shows that the detection results of the proposed algorithm for copy-paste tampered images are more accurate than those of the current algorithm for copy-paste tampered images, and it has higher robustness for content modifying such as rotation and zooming.