Title :
Gradient flows and geometric active contour models
Author :
Kichenassamy, Satyanad ; Kumar, Arun ; Olver, Peter ; Tannenbaum, Allen ; Yezzi, Anthony
Author_Institution :
Dept. of Math., Minnesota Univ., Minneapolis, MN, USA
Abstract :
In this paper, we analyze the geometric active contour models discussed previously from a curve evolution point of view and propose some modifications based on gradient flows relative to certain new feature-based Riemannian metrics. This leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus the snake is attracted very naturally and efficiently to the desired feature. Moreover, we consider some 3-D active surface models based on these ideas
Keywords :
computational geometry; computer vision; 3-D active surface models; curve evolution; feature-based Riemannian metrics; geometric active contour models; gradient flows; snake paradigm; Active contours; Books; Image edge detection; Mathematical model; Mathematics; Minimization methods; Nonlinear equations; Potential well; Shape; Solid modeling;
Conference_Titel :
Computer Vision, 1995. Proceedings., Fifth International Conference on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-8186-7042-8
DOI :
10.1109/ICCV.1995.466855