Bottom-Up Hierarchical Image Segmentation Using Region Competition and the Mumford-Shah Functional

This paper generalizes the methods in a previous paper in Pan, Y. et al, (2006) in two ways. First, a more comprehensive analysis of the initialization problem of the Chan-Vese models is given. Second, the image segmentation method proposed in Pan, Y. et al. (2006) is improved by applying bimodal cu...

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Bibliographic Details
Main Authors: Yongsheng Pan, Birdwell, J.D., Djouadi, S.M.
Format: Conference Proceeding
Language:English
Subjects:
Approximation methods
Humans
Image segmentation
Information technology
Laboratories
Mathematical analysis
Mathematical model
Minimization methods
Noise robustness
Pixel
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Summary:This paper generalizes the methods in a previous paper in Pan, Y. et al, (2006) in two ways. First, a more comprehensive analysis of the initialization problem of the Chan-Vese models is given. Second, the image segmentation method proposed in Pan, Y. et al. (2006) is improved by applying bimodal curve evolution with region competition. The improved method maintains the advantages of the previous method. It is efficient, stable in the presence of strong noise and able to handle complicated images. It outperforms the previous method for images with weak edges. Experimental results in this paper demonstrate these improvements
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2006.339