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

Authors:
Yongsheng Pan;J. Douglas Birdwell;Seddik M. Djouadi
Affiliations:
University of Tennessee, Knoxville, TN;University of Tennessee, Knoxville, TN;University of Tennessee, Knoxville, TN
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Year:
2006

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Abstract

This paper generalizes the methods in a previous paper [10] 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 [10] 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.