Title
Bottom-Up Hierarchical Image Segmentation Using Region Competition and the Mumford-Shah Functional
Abstract
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
Year
DOI
Venue
2006
10.1109/ICPR.2006.339
ICPR (2)
Keywords
DocType
Volume
bottom-up hierarchical image segmentation,hierarchical image segmentation,functional analysis,region competition,image segmentation,mumford-shah functional,previous method,comprehensive analysis,image segmentation method,chan-vese model,previous paper,complicated image,improved method,bimodal curve evolution,initialization problem,bottom up
Conference
2
ISSN
ISBN
Citations 
1051-4651
0-7695-2521-0
5
PageRank 
References 
Authors
0.57
6
3
Name
Order
Citations
PageRank
Yongsheng Pan1294.54
J. Douglas Birdwell25910.38
Seddik M. Djouadi321642.08