High performance template matching algorithm based on edge geometric features

Gray-scale correlation based template matching algorithm can hardly obtain accurate matching results in some conditions, a fast and high precision template matching method based on edge geometric features is proposed. Surface fitting method is used to obtain the gradient directions and sub-pixel coordinates of the edge points, which are used as the matching information in calculating the similarity between template and target. In order to satisfy the real-time requirement, image pyramid searching strategy is employed to accelerate the algorithm. Furthermore, the least square adjustment theory is adopted to calculate the sub-pixel positioning precision and precise rotation angle information. Experiment results demonstrate that the algorithm introduced in this paper can obtain good matching results in the case of target rotation, uniform or noon-uniform illumination disturbance, partial occlusion, and etc. Moreover, besides the stability, reliability and high precision, the proposed algorithm also can meet the real-time requirements. The repeat positioning precision of the algorithm is better than that of the GMF algorithm of the commercialized machine vision package of MIL8.0 from Matrox.