Multiclass object recognition based on texture linear genetic programming

Conferences Papers
  1. Gustavo Olague, Eva Romero, Leonardo Trujillo and Bir Bhanu. Multiclass Object Recognition Based on Texture Linear Genetic Programming. In EvoWorkshops. 2007, 291-300. BibTeX

    @inproceedings{DBLP:conf/evoW/OlagueRTB07,
    	author = "Gustavo Olague and Eva Romero and Leonardo Trujillo and Bir Bhanu",
    	title = "Multiclass Object Recognition Based on Texture Linear Genetic Programming",
    	booktitle = "EvoWorkshops",
    	year = 2007,
    	pages = "291-300",
    	ee = "http://dx.doi.org/10.1007/978-3-540-71805-5_32",
    	crossref = "DBLP:conf/evoW/2007",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    
  2. Mario Giacobini, Anthony Brabazon, Stefano Cagnoni, Gianni Di Caro, Rolf Drechsler, Muddassar Farooq, Andreas Fink, Evelyne Lutton, Penousal Machado, Stefan Minner, Michael O'Neill, Juan Romero, Franz Rothlauf, Giovanni Squillero, Hideyuki Takagi, Sima Uyar and Shengxiang Yang (eds.). Applications of Evolutinary Computing, EvoWorkshops 2007: EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog, Valencia, Spain, April11-13, 2007, Proceedings 4448. Springer, 2007. BibTeX

    @proceedings{DBLP:conf/evoW/2007,
    	editor = "Mario Giacobini and Anthony Brabazon and Stefano Cagnoni and Gianni Di Caro and Rolf Drechsler and Muddassar Farooq and Andreas Fink and Evelyne Lutton and Penousal Machado and Stefan Minner and Michael O'Neill and Juan Romero and Franz Rothlauf and Giovanni Squillero and Hideyuki Takagi and Sima Uyar and Shengxiang Yang",
    	title = "Applications of Evolutinary Computing, EvoWorkshops 2007: EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog, Valencia, Spain, April11-13, 2007, Proceedings",
    	booktitle = "EvoWorkshops",
    	publisher = "Springer",
    	series = "Lecture Notes in Computer Science",
    	volume = 4448,
    	year = 2007,
    	isbn = "978-3-540-71804-8",
    	bibsource = "DBLP, http://dblp.uni-trier.de"
    }
    
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.

Published in
Applications of Evolutionary Computing
Lecture Notes in Computer Science
Volume 4448
http://link.springer.com/chapter/10.1007%2F978-3-540-71805-5_32
(Nominated for the Best Paper Award at EvoIASP 2007)
Date of conference
11 - 13 Abril 2007
Pages
291 - 300
ISBN
0-7695-2372-2
Last modified onTuesday, 08 October 2013 03:54
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