关键词: 对象识别, Gestalt感知定律, 局部轮廓特征, 相邻直线段, 聚类

Abstract: In the natural scenario, it is difficult to extract a complete outline of the object because of background textures and light. This paper presents an object recognition method based on local contour feature. Firstly, the edge segments are split based on key points and merged based on Gestalt perception theory after the completion of extraction of the image edges. Secondly, it analyzes the contour feature made up of two or three adjacent segments. The semantic model of the contour feature that is made up of two adjacent segments is defined by the angle between the segments, the length and vectors of segments. The samples of local contour feature made up of two or three adjacent segments are drawn after the completion of decomposition of the template outline, and then the local contour feature made up of two or three adjacent segments is detected by combining the semantic model and matching the samples from the relations of the angle between the segments, the length and vector of segments. At last, the position points of detected local contour feature are obtained and grouped to recognize object. Experimental results show that the method can recognize the spacers and stock bridge dampers by processing the transmission line images acquired by UAV inspection.

Key words: object recognition, Gestalt perception theory, local contour feature, adjacent segments, group