DocumentCode :
2025440
Title :
Active Contours Based on Chambolle´s Mean Curvature Motion
Author :
Bresson, Xavier ; Chan, Tony F.
Author_Institution :
California Univ., Los Angeles
Volume :
1
fYear :
2007
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
This paper proposes an algorithm to solve most of existing active contour problems based on the approach of mean curvature motion proposed by Chambolle (2004) and the image denoising model of Rudin, Osher and Fatemi (ROF) (1992). More precisely, the motion of active contours is discretized by the ROF model applied to the signed distance of the evolving contour. The advantage of this new discretization scheme is to use a time step much larger than in standard explicit schemes, which means that less iterations are needed to converge to the steady state solution. We present results on 2-D natural images.
Keywords :
convergence of numerical methods; curve fitting; edge detection; image denoising; image motion analysis; image segmentation; iterative methods; object detection; Chambolle mean curvature motion; ROF model; active contour problems; boundary detection; convergence; discretization scheme; image denoising model; image segmentation; iteration process; object extraction; region detection; signed distance function; Active contours; Biomedical imaging; Image converters; Image denoising; Image edge detection; Image processing; Image segmentation; Level set; Object detection; Steady-state; Image segmentation; ROF model; active contour; object extraction; signed distance function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1522-4880
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2007.4378884
Filename :
4378884
Link To Document :
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