Faculty of Information Technology, BUT

Publication Details

Acceleration of Evolutionary Image Filter Design Using Coevolution in Cartesian GP

DRAHOŠOVÁ Michaela and SEKANINA Lukáš. Acceleration of Evolutionary Image Filter Design Using Coevolution in Cartesian GP. Lecture Notes in Computer Science, vol. 2012, no. 7491, pp. 163-172. ISBN 978-3-642-32936-4. ISSN 0302-9743. Available from: http://link.springer.com/chapter/10.1007%2F978-3-642-32937-1_17
Czech title
Akcelerace evolučního návrhu obrazových filtrů s použitím koevoluce v kartézském GP
Type
journal article
Language
english
Authors
URL
Keywords
Cartesian genetic programming, coevolution, fitness modeling, image filter design.
Abstract
The aim of this paper is to accelerate the task of evolutionary image filter design using coevolution of candidate filters and training vectors subsets. Two coevolutionary methods are implemented and compared for this task in the framework of Cartesian Genetic Programming (CGP). Experimental results show that only 15-20 % of original test vectors are needed to find an image filter which provides the same quality of filtering as the best filter evolved using the standard CGP which utilizes the whole training set. Moreover, the median time of evolution was reduced 2.99 times in comparison with the standard CGP.
Published
2012
Pages
163-172
Journal
Lecture Notes in Computer Science, vol. 2012, no. 7491, ISSN 0302-9743
Book
The 12th International Conference on Parallel Problem Solving from Nature
ISBN
978-3-642-32936-4
Publisher
Springer Verlag
Place
Berlin, DE
DOI
BibTeX
@ARTICLE{FITPUB9967,
   author = "Michaela Draho\v{s}ov\'{a} and Luk\'{a}\v{s} Sekanina",
   title = "Acceleration of Evolutionary Image Filter Design Using Coevolution in Cartesian GP",
   pages = "163--172",
   booktitle = "The 12th International Conference on Parallel Problem Solving from Nature",
   journal = "Lecture Notes in Computer Science",
   volume = 2012,
   number = 7491,
   year = 2012,
   location = "Berlin, DE",
   publisher = "Springer Verlag",
   ISBN = "978-3-642-32936-4",
   ISSN = "0302-9743",
   doi = "10.1007/978-3-642-32937-1\_17",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/9967"
}
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