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Pattern recognition from compressed labelled trees of fuzzy regions

  • Laurent Wendling
  • Jacky Desachy
  • Alain Paries
Poster Session A: Color & Texture, Enhancement Image Analysis & Pattern Recognition, Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)

Abstract

In this paper, a method of pattern recognition based on images split into a set of trees composed of fuzzy regions is presented. First, a fuzzy segmentation based on possibilistic c-means is carried out in the raster image. Fuzzy support have been defined from a first level cut. On each cluster, a fuzzy region is assumed to be a convex combination of sets with associated features. A set of sample trees is achieved from the application of the segmentation algorithm on characteristic objects. Then, a tree isomorphism to recognize is defined to recognize an object. At last, a new tree compression method is introduced to decrease the complexity when we have to manage with a large set of trees.

Keywords

Fuzzy Regions Tree Isomorphism Directed Acyclic Graph Compression Pattern Recognition 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Laurent Wendling
    • 1
  • Jacky Desachy
    • 1
  • Alain Paries
    • 2
  1. 1.Université Paul Sabatier (Toulouse III) IRIT 118Toulouse CedexFrance
  2. 2.Université Bordeaux ITalence Cedex

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