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Pattern recognition of strong graphs based on possibilistic c-means and k-formulae matching

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Fuzzy Logic in Artificial Intelligence (FLAI 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1566))

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Abstract

A new graph matching approach based on 1D information is presented. Each node of the matched graphs represents a fuzzy region (fuzzy segmentation step). Each couple of nodes is linked by a relational histogram which can be assumed to the attraction of two regions following a set of directions. This attraction is computed by a continuous function, depending on the distance of the matched objects. Each case of the histogram corresponds to a particular direction. Then, relational graph computed from strong scenes are matched.

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Authors and Affiliations

  1. Université Paul Sabatier-IRIT, 118, route de Narbonne, 31062, Toulouse Cedex, France

    L. Wendling & J. Desachy

Authors
  1. L. Wendling
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  2. J. Desachy
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Editor information

Anca L. Ralescu James G. Shanahan

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© 1999 Springer-Verlag Berlin Heidelberg

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Wendling, L., Desachy, J. (1999). Pattern recognition of strong graphs based on possibilistic c-means and k-formulae matching. In: Ralescu, A.L., Shanahan, J.G. (eds) Fuzzy Logic in Artificial Intelligence. FLAI 1997. Lecture Notes in Computer Science, vol 1566. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095078

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  • DOI: https://doi.org/10.1007/BFb0095078

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66374-4

  • Online ISBN: 978-3-540-48358-8

  • eBook Packages: Springer Book Archive

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