A Statistical Approach to Snakes for Bimodal and Trimodal Imagery

In this paper, 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 values of a predetermined 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.

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Anthony J. Yezzi, Andy Tsai, Alan S. Willsky
• Keywords: Active Contours, Computer Vision, Edge-based Snake Algorithms, ICCV 1999, Image Derivatives, Local Image Information