Synergism in Low Level Vision

Christopher M. Christoudias(1), Bogdan Georgescu(2) and Peter Meer(1,2)

(1) Department of Electrical and Computer Engineering
(2) Department of Computer Science
Rutgers University, Piscataway, NJ 08854, USA

Guiding image segmentation with edge information is an often employed strategy in low level computer vision. To improve the trade-off between the sensitivity of homogeneous region delineation and the oversegmentation of the image, we have incorporated a recently proposed edge magnitude/confidence map into a color image segmenter based on the mean shift procedure. The new method can recover regions with weak but sharp boundaries and thus can provide a more accurate input for high level interpretation modules. The Edge Detection and Image SegmentatiON (EDISON) system, available for download, implements the proposed technique and provides a complete toolbox for discontinuity preserving filtering, segmentation and edge detection.

16th International Conference on Pattern Recognition., Quebec City, Canada, August 2002, vol. IV, 150-155.
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