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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Bibliographic Details
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
Online Access:Get full text
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Summary: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.
ISSN:0167-8655
1872-7344
DOI:10.1016/j.patrec.2006.07.001