A curve tracing algorithm using level set based affine transform

Extracting centrelines from an unordered data set is an important problem in image processing and pattern recognition. The key strategy of existing methods is to find a curve placed at the middle of the data points. However, if the data set contains noise, these algorithms will converge to a local m...

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Published in:	Pattern recognition letters Vol. 28; no. 2; pp. 181 - 196
Main Authors:	Lam, B.S.Y., Yan, H.
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 15.01.2007 Elsevier
Subjects:	Affine transform Applied sciences Exact sciences and technology Fuzzy curve-tracing (FCT) algorithm Image processing Information, signal and communications theory Level set method Pattern recognition Pattern thinning Signal processing Skeletonization Telecommunications and information theory Fuzzy curve-tracing (FCT) algorithm Skeletonization Level set method Pattern thinning Affine transform Performance evaluation Image processing Pattern recognition Affine transformation Algorithm Edge detection Shape detection
ISSN:	0167-8655, 1872-7344
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Abstract	Extracting centrelines from an unordered data set is an important problem in image processing and pattern recognition. The key strategy of existing methods is to find a curve placed at the middle of the data points. However, if the data set contains noise, these algorithms will converge to a local minimum. In this paper, we propose a new technique, which combines the level set and affine transform methods. In this approach, the user-defined initial curve is driven towards the object data. Experimental results show that the proposed method can enhance the performance of a class of curve extraction algorithms effectively.
AbstractList	Extracting centrelines from an unordered data set is an important problem in image processing and pattern recognition. The key strategy of existing methods is to find a curve placed at the middle of the data points. However, if the data set contains noise, these algorithms will converge to a local minimum. In this paper, we propose a new technique, which combines the level set and affine transform methods. In this approach, the user-defined initial curve is driven towards the object data. Experimental results show that the proposed method can enhance the performance of a class of curve extraction algorithms effectively.
Author	Lam, B.S.Y. Yan, H.
Author_xml	– sequence: 1 givenname: B.S.Y. surname: Lam fullname: Lam, B.S.Y. email: 50005347@student.cityu.edu.hk organization: Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong – sequence: 2 givenname: H. surname: Yan fullname: Yan, H. organization: Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
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Keywords	Fuzzy curve-tracing (FCT) algorithm Skeletonization Level set method Pattern thinning Affine transform Performance evaluation Image processing Pattern recognition Affine transformation Algorithm Edge detection Shape detection
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SubjectTerms	Affine transform Applied sciences Exact sciences and technology Fuzzy curve-tracing (FCT) algorithm Image processing Information, signal and communications theory Level set method Pattern recognition Pattern thinning Signal processing Skeletonization Telecommunications and information theory
Title	A curve tracing algorithm using level set based affine transform
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