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Typical Segment Descriptors: A New Method for Shape Description and Identification

  • Nancy Aimé Alvarez-Roca
  • José Ruiz-Shulcloper
  • Jose M. Sanchiz-Marti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)

Abstract

In this paper we introduce a new method for recognizing and classifying images based on concepts derived from Logical Combinatorial Pattern Recognition (LCPR). The concept of Typical Segment Descriptor (TSD) is introduced, and algorithms are presented to compute TSDs sets from several chain code representations, like the Freeman chain code, the first differences chain code, and the vertex chain code. The typical segment descriptors of a shape are invariant to changes in the starting point, translations and rotations, and can be used for partial occlusion detection. We show several results of shape description problems pointing out the reduction in the length of the description achieved.

Keywords

Shape Description Chain Code Circular Index Supervise Pattern Recognition Learning Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Nancy Aimé Alvarez-Roca
    • 1
  • José Ruiz-Shulcloper
    • 2
  • Jose M. Sanchiz-Marti
    • 3
  1. 1.Departamento de Ciencia de la ComputaciónUniversidad de OrienteSantiago de CubaCuba
  2. 2.Laboratorio de Reconocimiento de PatronesInstituto de Cibernética, Matemáticas y FísicaLa HabanaCuba
  3. 3.Departamento de Ingeniería y Ciencia de los ComputadoresUniversidad Jaume ICastellónSpain

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