Fast object recognition using dynamic programming from combination of salient line groups

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This paper presents a new method of grouping and matching line segments to recognize objects. We propose a dynamic programming-based formulation extracting salient line patterns by defining a robust and stable geometric representation that is based on perceptual organizations. As the endpoint proximity, we detect several junctions from image lines. We then search for junction groups by using the collinear constraint between the junctions. Junction groups similar to the model are searched in the scene, based on a local comparison. A DP-based search algorithm reduces the time complexity for the search of the model lines in the scene. The system is able to find reasonable line groups in a short time. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2003-01
Language
English
Article Type
Article
Keywords

INVARIANT; STEREO

Citation

PATTERN RECOGNITION, v.36, no.1, pp.79 - 90

ISSN
0031-3203
URI
http://hdl.handle.net/10203/20502
Appears in Collection
EE-Journal Papers(저널논문)
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