DocumentCode :
3315321
Title :
A level set algorithm for minimizing the Mumford-Shah functional in image processing
Author :
Chan, Tony E. ; Vese, Luminita A.
Author_Institution :
Dept. of Math., California Univ., Los Angeles, CA, USA
fYear :
2001
fDate :
2001
Firstpage :
161
Lastpage :
168
Abstract :
We show how the piecewise-smooth Mumford-Shah segmentation problem can be solved using the level set method of Osher and Sethian (1988). The obtained algorithm can be simultaneously used to denoise, segment, detect-extract edges, and perform active contours. The proposed model is also a generalisation of a previous active contour model without edges, proposed by the authors in Chan et al., (2001), and of its extension to the case with more than two segments for piecewise-constant segmentation Chan et al., (2000). Based on the four color theorem, we can assume that in general, at most two level set functions are sufficient to detect and represent distinct objects of distinct intensities, with triple junctions, or T-junctions
Keywords :
edge detection; functional equations; image segmentation; minimisation; piecewise constant techniques; set theory; Mumford-Shah functional; T-junctions; active contours; denoising; edge detection; edge extraction; four color theorem; image processing; level set algorithm; minimization; piecewise-smooth segmentation; triple junctions; Active contours; Contracts; Image edge detection; Image processing; Image segmentation; Level set; Mathematics; Object detection; Phase detection; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Variational and Level Set Methods in Computer Vision, 2001. Proceedings. IEEE Workshop on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7695-1278-X
Type :
conf
DOI :
10.1109/VLSM.2001.938895
Filename :
938895
Link To Document :
بازگشت