Synergism in Low Level Vision

Authors

  • Christopher M. Christoudias Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, 08854-8058, USA
  • Bogdan Georgescu Computer Science Department, Rutgers University, Piscataway, NJ, 08854-8058, USA
  • Peter Meer Electrical and Computer Engineering Department, Computer Science Department, Rutgers University, Piscataway, NJ, 08854-8058, USA

Abstract

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, segmentationand edge detection.

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Published

2002-09-30

How to Cite

Christoudias, C. M. ., Georgescu, B. ., & Meer, P. . (2002). Synergism in Low Level Vision. The Rutger Scholar, 4. Retrieved from https://rutgersscholar.libraries.rutgers.edu/index.php/scholar/article/view/50

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Articles