A statistical approach to snakes for bimodal and trimodal imagery

Author

Yezzi, Anthony, Jr. ; Tsai, Andy ; Willsky, Alan

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., MIT, Cambridge, MA, USA

Volume

2

fYear

1999

fDate

1999

Firstpage

898

Abstract

We describe a new region based approach to active contours for segmenting images composed 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 valves 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 robustness compared to most edge based snake algorithms

Keywords

computational geometry; edge detection; image segmentation; statistical analysis; active contours; bimodal imagery; curve evolutions; edge based snake algorithms; geometrically determined subsets; global image information; image derivatives; image segmentation; local image information; noise robustness; region based approach; statistical approach; trimodal imagery; Acoustic noise; Active contours; Clustering algorithms; Equations; Image edge detection; Image segmentation; Level set; Noise robustness; Statistics; Subcontracting;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on

Conference_Location

Kerkyra

Print_ISBN

0-7695-0164-8

Type

conf

DOI

10.1109/ICCV.1999.790317

Filename

790317