A Fast Algorithm for Dominant Point Detection on Chain-Coded Contours

Dominant point detection is the task of segmenting a contour at distinguished points of high local curvature. A new, fast algorithm for automatic detection of such points is proposed. The contour is smoothed and differentiated in the x and y direction separately. Points with local extrema in the curvature are considered candidate dominant points. A discriminating function composed of the curvature and its derivative is computed for each candidate point and compared to a threshold. The degree of smoothing and the threshold on the discriminating function are the two input parameters to the algorithm. The computational cost is linear in the length of the contour and sufficiently low for real-time video (25–30Hz) processing of reasonable sized contours. The algorithm matches the performance of a human observer on many realistic contours, has excellent location accuracy and produces few spurious points.

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