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Fuzzy cognitive maps for stereovision matching

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Pajares Martinsanz, Gonzalo and Cruz García, Jesús Manuel de la (2006) Fuzzy cognitive maps for stereovision matching. Pattern Recognition, 39 (11). pp. 2101-2114. ISSN 0031-3203

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Official URL: http://dx.doi.org/10.1016/j.patcog.2006.04.003




Abstract

This paper outlines a method for solving the stereovision matching problem using edge segments as the primitives. In stereovision matching the following constraints are commonly used: epipolar, similarity, smoothness, ordering and uniqueness. We propose a new matching strategy under a fuzzy context in which such constraints are mapped. The fuzzy context integrates both Fuzzy Clustering and Fuzzy Cognitive Maps. With such purpose a network of concepts (nodes) is designed, each concept represents a pair of primitives to be matched. Each concept has associated a fuzzy value which determines the degree of the correspondence. The goal is to achieve high performance in terms of correct matches. The main findings of this paper are reflected in the use of the fuzzy context that allows building the network of concepts where the matching constraints are mapped. Initially, each concept value is loaded via the Fuzzy Clustering and then updated by the Fuzzy Cognitive Maps framework. This updating is achieved through the influence of the remainder neighboring concepts until a good global matching solution is achieved. Under this fuzzy approach we gain quantitative and qualitative matching correspondences. This method works as a relaxation matching approach and its performance is illustrated by comparative analysis against some existing global matching methods. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.


Item Type:Article
Additional Information:

© 2006 Pattern Recognition Society.
Part of the work has been performed under Projects CICYT
DPI2002-02924 and CICYT TAP94-0832-C02-01.
The authors wish to acknowledge the constructive recommendations
provided by the reviewers.

Uncontrolled Keywords:Support Vector Machines, Probabilistic Relaxation, Vision, Algorithm, Images, Window
Subjects:Sciences > Computer science
ID Code:23688
Deposited On:27 Nov 2013 10:36
Last Modified:07 Feb 2014 11:06

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