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Corner detection is a crucial prerequisite for motion detection, image matching, video tracking, 3D reconstruction, and target recognition. The precision of corner detection has a direct bearing on the experimental outcomes. In order to better comprehend the development status of corner detection technology, the corner detection methods and associated enhancements are summarized and analyzed based on the three classifications of existing corner detection algorithms. FAST, SUSAN, SIFT, and Shi-Tomas are chosen for experimental comparison, and the results of the experiment are provided. Different practical applications have different corner detection requirements, and various corner detection algorithms can also be combined. Through a summary and analysis of the existing corner detection technology, this paper serves as a guide for the selection and development of corner detection technology for practical applications.