DocumentCode :
595400
Title :
A genetic algorithm based approach for combining binary image operators
Author :
Dornelles, M.M. ; Hirata, Nina S. T.
Author_Institution :
Univ. Estadual de Santa Cruz & Univ. of Sao Paulo, Santa Cruz, Brazil
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
3184
Lastpage :
3187
Abstract :
Combining several binary image operators, each one based on different windows, has proven to be an effective way to produce operators with better performance than designing single operators based on one window only. To facilitate the combination task that so far is done manually, we propose a genetic algorithm (GA) based approach. It consists of the definition of a collection of candidate windows and the use of a GA to select a subset of them that will determine the operators to be combined. Experimental results show that the proposed GA based approach produces combinations that are consistently better than those obtained manually, and indicate that the proposed window collections do contain relevant windows.
Keywords :
genetic algorithms; image classification; binary classifier; binary image operators; candidate window collection; combination task; genetic algorithm; Biological cells; Genetic algorithms; Measurement; Pattern recognition; Sociology; Statistics; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460841
Link To Document :
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