DocumentCode :
2500038
Title :
Level Set Based Segmentation Using Local Feature Distribution
Author :
Xie, Xianghua
Author_Institution :
Dept. of Comput. Sci., Swansea Univ., Swansea, UK
fYear :
2010
fDate :
23-26 Aug. 2010
Firstpage :
2780
Lastpage :
2783
Abstract :
We propose a level set based framework to segment textured images. The snake deforms in the image domain in searching for object boundaries by minimizing an energy functional, which is defined based on dynamically selected local distribution of orientation invariant features. We also explore the user initialization to simplify the segmentation and improve accuracy. Experimental results on both synthetic and real data show significant improvements compared to direct modeling of filtering responses or piecewise constant modeling.
Keywords :
filtering theory; image segmentation; image texture; set theory; filtering responses; level set based segmentation; local feature distribution; orientation invariant features; piecewise constant modeling; Active contours; Histograms; Image segmentation; Level set; Minimization; Nonhomogeneous media; Pixel; Active Contour; Image Segmentation; Level Set; Texture Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.681
Filename :
5597031
Link To Document :
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