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Moment-based contour segmentation using multiple segmentation primitives

Śluzek A.

Machine Graphics and Vision

1998

Vol. 7, No. 1/2

269-279

The paper presents a new technique of segmentating digital contours using multiple segmentation primitives. Therefore segmentation results are a combination of line segments, arcs. corners,etc., depending on how well these shapesmath the orginal contour. In yhr first step, the prospective instances of all avaible segmentation primitives are detected within the input digital contours. Then, the detected instances are ranked according to how accurately they fit the corresponding fragment of the contour. Finally, the top-rank segmantation primitives are selected one by one until the whole contour is approximeted. The algorithms has relatively low computational complexity, and it allows paraqllel implementation. Moreover, the algorithm is not sensitive to the performance of edge detectors so that similar results are produced no matter what edge detector has extracted contours from the original image. Therefore, if the quality of camera-captured images is satisfactofily high, the algorithm can analyse them whitout any pre- processing required (except, of course, edge detection).