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Curve Segmentation Under Partial Occlusion
May 1994 (vol. 16 no. 5)
pp. 513-519

2-D shape boundary segmentation is required as a fundamental and important stage in the recognition of partially occluded objects. We introduce here a new segmentation method capable of extracting a controlled number of segments along a smooth boundary curve. This new approach is invariant to similarity transformation, and partial occlusion has only marginal influence on the segmentation of the visible part. The basic concept is to transform the curve into another one which intersects itself. Points of intersection of the new curve are re-transformed to the original curve and serve as endpoints of segments. Properties of the transform are discussed, and conditions for existence of intersection points are given. Simulation results of gray level images are presented, and advantages of our method over conventional approaches relying on singular points of the curvature are discussed.

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Index Terms:
image segmentation; image recognition; transforms; curve segmentation; partial occlusion; 2-D shape boundary segmentation; partially occluded object recognition; smooth boundary curve; similarity transformation invariance; intersection point existence conditions; gray level images
N. Katzir, M. Lindenbaum, M. Porat, "Curve Segmentation Under Partial Occlusion," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 5, pp. 513-519, May 1994, doi:10.1109/34.291446
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