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<p><b>Abstract</b>—The problem of corner detection on planar curves is examined based on human perception of local graphic features. First, a set of fuzzy patterns of contour points are established. Then, corner detection is characterized as a fuzzy classification problem that contains three stages: evaluation, classification, and location. Compared with existing methods, the proposed approach is superior in that it explains the curve, instead of simple labeling, and it performs based on human perception. Experimental results on shapes of various complexities are presented. The performance with respect to noise is also addressed.</p>
Corner detection, dominant point detection, digital curves, curve description, feature extraction, shape analysis, fuzzy reasoning, fuzzy pattern recognition.

W. Chen and L. Li, "Corner Detection and Interpretation on Planar Curves Using Fuzzy Reasoning," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 21, no. , pp. 1204-1210, 1999.
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