Multiclass Object Recognition Based on Texture Linear Genetic Programming

Authors:
Gustavo Olague;Eva Romero;Leonardo Trujillo;Bir Bhanu
Affiliations:
CICESE, Km. 107 carretera Tijuana-Ensenada, Mexico;CICESE, Km. 107 carretera Tijuana-Ensenada, Mexico;CICESE, Km. 107 carretera Tijuana-Ensenada, Mexico;Center for Research in Intelligent Systems, University of California, Riverside, USA
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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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.