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Contour defects detection of the chamfering fine-blanking parts is very important to increase productivity and ensure products desired quality. However, the contour of chamfering fine-blanking parts are irregular, the image itself exists ambiguity due to pixels of target’s edge and background with gradual transition, and the feature of contour defect is very weak. Thus the contour extraction algorithm and a defect recognition method with fuzzy sets are proposed to detect defects and mark the location. Firstly, the fuzzy set is employed to strengthen the edge information, suppress noises and extract the contour accurately and effectively. According to the set of points and line features of the extracted contour, the method of obtaining location and attitude of stamping parts through HOHGH transformation are designed. And then, the location and attitude of stamping parts to be detected will be aligned precisely in real time using the pose feature of the stamping template image. The difference similarity matching algorithm is utilized to identify the defects. Some experimental results show that more than 0.4% small defects of the total part can be identified and located quickly and exactly which meets industrial inspection requirements.