Initialization Techniques for Segmentation with the Chan-Vese Model

This paper introduces an effective initialization approach for segmentation using the Chan-Vese model. The initial curve is found by searching among the extremals of the fidelity term, as a form of intelligent thresholding where the regularity of the threshold level is incorporated. The method has a...

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Bibliographic Details
Published in18th International Conference on Pattern Recognition (ICPR'06) Vol. 2; pp. 171 - 174
Main Authors Solem, J.E., Overgaard, N.C., Heyden, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2006
Subjects
Active contours
Image segmentation
Level set
Mathematical model
Mathematics
Pattern recognition
Statistics
Surface treatment
Testing
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Summary:This paper introduces an effective initialization approach for segmentation using the Chan-Vese model. The initial curve is found by searching among the extremals of the fidelity term, as a form of intelligent thresholding where the regularity of the threshold level is incorporated. The method has a nice connection to the curvature of the optimal initial partition boundary. The method is tested on several examples and gives considerable increase in performance
ISBN:0769525210
9780769525211
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2006.713