DocumentCode
2867720
Title
Image Segmentation Using Curve Evolution and Anisotropic Diffusion: An Integrated Approach
Author
Pan, Yongsheng ; Birdwell, J. Douglas ; Djouadi, Seddik M.
Author_Institution
Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN
fYear
2005
fDate
14-14 Dec. 2005
Firstpage
387
Lastpage
394
Abstract
In this paper, a new model is proposed for image segmentation that integrates the curve evolution and anisotropic diffusion methods. The curve evolution method, utilizing both gradient and region information, segments an image into multiple regions. During the evolution of the curve, anisotropic diffusion is adaptively applied to the image to remove noise while preserving boundary information. Coupled partial differential equations (PDE´s) are used to implement the method. Experimental results show that the proposed model is successful for complex images with high noise
Keywords
curve fitting; gradient methods; image segmentation; partial differential equations; anisotropic diffusion method; boundary information; complex image segmentation; coupled partial differential equation; curve evolution method; gradient information; noise removal; region information; Active contours; Active noise reduction; Anisotropic magnetoresistance; Image segmentation; Information technology; Laboratories; Level set; Object detection; Partial differential equations; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia, Seventh IEEE International Symposium on
Conference_Location
Irvine, CA
Print_ISBN
0-7695-2489-3
Type
conf
DOI
10.1109/ISM.2005.68
Filename
1565859
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