In order to realize accurate and rapid image matching, this paper proposes a corner matching algorithm based on corner point detection and the descriptor. Firstly, in the curvature scale space, the corner points of the image at different scales are detected, and the unstable corner points are removed.Secondly, based on the accuracy of the curvature describing the contour of the image, the neighborhood is divided into 3×4 sub-neighborhoods taking the character points as the center, the 4-dimensional vector features in the sub-neighborhood are calculated, such as the Gaussian weighted curvature of the contour curve points, and a 48-dimensional descriptor is built.Since the CSS corner point detection includes curvature calculation, the quadratic calculation of the curvature is avoided when generating the descriptor, and thus the matching speed is improved. Finally, a binary distance method is proposed to match the descriptors to further optimize the matching speed. Experiments have proved that, with the assurance of accuracy, the CSS fast matching algorithm can shorten the matching time to a great extent and achieve satisfying matching results under rotation and illumination changes.