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Object Recognition Using Hausdorff Distance and Image Matching Algorithm
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 Title & Authors
Object Recognition Using Hausdorff Distance and Image Matching Algorithm
Kim, Dong-Gi; Lee, Wan-Jae; Gang, Lee-Seok;
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The pixel information of the object was obtained sequentially and pixels were clustered to a label by the line labeling method. Feature points were determined by finding the slope for edge pixels after selecting the fixed number of edge pixels. The slope was estimated by the least square method to reduce the detection error. Once a matching point was determined by comparing the feature information of the object and the pattern, the parameters for translation, scaling and rotation were obtained by selecting the longer line of the two which passed through the matching point from left and right sides. Finally, modified Hausdorff Distance has been used to identify the similarity between the object and the given pattern. The multi-label method was developed for recognizing the patterns with more than one label, which performs the modified Hausdorff Distance twice. Experiments have been performed to verify the performance of the proposed algorithm and method for simple target image, complex target image, simple pattern, and complex pattern as well as the partially hidden object. It was proved via experiments that the proposed image matching algorithm for recognizing the object had a good performance of matching.
Line Labeling;Multi Label;Feature Point;Matching Point;
 Cited by
물체인식을 위한 영상분할 기법과 퍼지 알고리듬을 이용한 유사도 측정,김동기;이성규;이문욱;강이석;

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