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Multiclass Object Recognition Based on Texture Linear Genetic Programming

  • Gustavo Olague
  • Eva Romero
  • Leonardo Trujillo
  • Bir Bhanu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4448)

Abstract

This paper presents a linear genetic programming approach, that solves simultaneously the region selection and feature extraction tasks, that are applicable to common image recognition problems. The method searches for optimal regions of interest, using texture information as its feature space and classification accuracy as the fitness function. Texture is analyzed based on the gray level cooccurrence matrix and classification is carried out with a SVM committee. Results show effective performance compared with previous results using a standard image database.

Keywords

Genetic Programming Training Image Gray Level Cooccurrence Matrix Linear Genetic Programming Cooperative Coevolution 
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 2007

Authors and Affiliations

  • Gustavo Olague
    • 1
  • Eva Romero
    • 1
  • Leonardo Trujillo
    • 1
  • Bir Bhanu
    • 2
  1. 1.CICESE, Km. 107 carretera Tijuana-EnsenadaMexico
  2. 2.Center for Research in Intelligent Systems, University of California, RiversideUSA

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