DocumentCode
507334
Title
A Fast Segmentation Method Based on Curve Evolution Model and Edgeflow
Author
Xie Qing-Song ; Li Jin-jiang ; Yuan Da
Author_Institution
Sch. of Comput. Sci. & Technol., Shandong Inst. of Bus. & Technol., Yantai, China
Volume
5
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
307
Lastpage
310
Abstract
This paper proposes a high-accuracy edge contour extraction algorithm based on curve evolution model and edgeflow. The approach automatically detect boundaries, and change of topology in terms of the edgeflow fields. We present the numerical implementation and the experimental results based on the semi-implicit method. Experimental results are given to demonstrate the feasibility of the proposed method in extracting contour from the blurred edge and high-noise images.
Keywords
edge detection; image segmentation; blurred edge; curve evolution model; edgeflow; fast segmentation method; high-accuracy edge contour extraction; high-noise images; semi-implicit method; Change detection algorithms; Computer science; Deconvolution; Filtering; Filters; Fuzzy systems; Image edge detection; Iterative methods; Partial differential equations; Topology; Curve Evolution; Edgeflow; Segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.80
Filename
5360611
Link To Document