Similar circular object recognition method based on local contour feature in natural scenario
BAN Xiaokun1, HAN Jun1, LU Dongming1, WANG Wanguo2, LIU Liang2
1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China; 2. Electric Power Robotics Laboratory of State Grid Corporation of China, Shandong Electric Power Research Institute, Jinan Shangdong 250002, China
Abstract：In the natural scenario, it is difficult to extract a complete outline of the object because of background textures, light and occlusion. Therefore an object recognition method based on local contour feature was proposed. Local contour feature of this paper formed by chains of 2-adjacent straight and curve contour segments (2AS). First, the angle of the adjacent segments, the segment length and the bending strength were analyzed, and the semantic model of the 2AS contour feature was defined. Then on the basis of the relative position relation between object's 2AS features, the 2AS mutual relation model was defined. Second, the 2AS semantic model of the object template primarily matched with the 2AS features of the test image, then 2AS mutual relation model of object template accurately matched with the 2AS features of the test image. At last, the pairs of 2AS of detected local contour features were obtained and repeatedly grouped, then grouped objects were verified according to the 2AS mutual relation model of object template. The contrast experiment with the 2AS feature algorithm with similar straight-line chains, the proposed algorithm has higher accuracy, low false positive rate and miss rate in the recognition of grading ring, then the method can more effectively recognize the grading ring.
班孝坤, 韩军, 陆冬明, 王万国, 刘俍. 自然场景中基于局部轮廓特征的类圆对象识别方法[J]. 计算机应用, 2016, 36(5): 1399-1403.
BAN Xiaokun, HAN Jun, LU Dongming, WANG Wanguo, LIU Liang. Similar circular object recognition method based on local contour feature in natural scenario. Journal of Computer Applications, 2016, 36(5): 1399-1403.
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2016, Vol. 36 
