A Statistical Approach to Snakes for Bimodal and Trimodal Imagery

Yezzi, Anthony; Tsai, Andy; Willsky, Alan

Title:

A Statistical Approach to Snakes for Bimodal and Trimodal Imagery

dc.contributor.author	Yezzi, Anthony
dc.contributor.author	Tsai, Andy
dc.contributor.author	Willsky, Alan
dc.contributor.corporatename	Georgia Institute of Technology. School of Electrical and Computer Engineering	en_US
dc.contributor.corporatename	Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science	en_US
dc.date.accessioned	2013-09-26T11:50:25Z
dc.date.available	2013-09-26T11:50:25Z
dc.date.issued	1999-09
dc.description	© 1999 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.description	DOI: 10.1109/ICCV.1999.790317
dc.description.abstract	In this paper, we describe a new region-based approach to active contours for segmenting images com- posed of two or three types of regions characterizable by a given statistic. The essential idea is to derive curve evolutions which separate two or more values of a pre- determined set of statistics computed over geometrically determined subsets of the image. Both global and local image information is used to evolve the active contour. Image derivatives, however, are avoided, thereby giving rise to a further degree of noise robust- ness compared to most edge-based snake algorithms.	en_US
dc.embargo.terms	null	en_US
dc.identifier.citation	Yezzi, A., Jr.; Tsai, A.; & Willsky, A. (1999). "A Statistical Approach to Snakes for Bimodal and Trimodal Imagery". Proceedings of the Seventh IEEE International Conference on Computer Vision (ICCV 1999), Vol. 2, September 1999, pp.898-903.	en_US
dc.identifier.doi	10.1109/ICCV.1999.790317
dc.identifier.uri	http://hdl.handle.net/1853/49139
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.publisher.original	Institute of Electrical and Electronics Engineers
dc.subject	Active contours	en_US
dc.subject	Curve evolutions	en_US
dc.subject	Image segmentation	en_US
dc.subject	Noise robustness	en_US
dc.subject	Snakes	en_US
dc.subject	Statistics	en_US
dc.title	A Statistical Approach to Snakes for Bimodal and Trimodal Imagery	en_US
dc.type	Text
dc.type.genre	Proceedings
dspace.entity.type	Publication
local.contributor.author	Yezzi, Anthony
local.contributor.corporatename	School of Electrical and Computer Engineering
local.contributor.corporatename	College of Engineering
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