A GP Artificial Ant for image processing:
preliminary experiments with EASEA
E. Bolis, C. Zerbi, P. Collet, J. Louchet, and E. Lutton. Genetic Programming, Proceedings of EuroGP'2001, volume 2038 of LNCS, page 246--255. Lake Como, Italy, Springer-Verlag, (18-20 April 2001)
Abstract
This paper describes how animat-based "food
foraging" techniques may be applied to the design of
low-level image processing algorithms. First, we show
how we implemented the food foraging application using
the EASEA software package. We then use this technique
to evolve an animat and learn how to move inside images
and detect high-gradient lines with a minimum
exploration time. The resulting animats do not use
standard "scanning + filtering" techniques but
develop other image exploration strategies close to
contour tracking. Experimental results on grey level
images are presented.
%0 Conference Paper
%1 bolis:2001:EuroGP
%A Bolis, Enzo
%A Zerbi, Christian
%A Collet, Pierre
%A Louchet, Jean
%A Lutton, Evelyne
%B Genetic Programming, Proceedings of EuroGP'2001
%C Lake Como, Italy
%D 2001
%E Miller, Julian F.
%E Tomassini, Marco
%E Lanzi, Pier Luca
%E Ryan, Conor
%E Tettamanzi, Andrea G. B.
%E Langdon, William B.
%I Springer-Verlag
%K Animat Contour EASEA, Image algorithms, detection, genetic processing, programming,
%P 246--255
%T A GP Artificial Ant for image processing:
preliminary experiments with EASEA
%U http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=246
%V 2038
%X This paper describes how animat-based "food
foraging" techniques may be applied to the design of
low-level image processing algorithms. First, we show
how we implemented the food foraging application using
the EASEA software package. We then use this technique
to evolve an animat and learn how to move inside images
and detect high-gradient lines with a minimum
exploration time. The resulting animats do not use
standard "scanning + filtering" techniques but
develop other image exploration strategies close to
contour tracking. Experimental results on grey level
images are presented.
%@ 3-540-41899-7
@inproceedings{bolis:2001:EuroGP,
abstract = {This paper describes how animat-based {"}food
foraging{"} techniques may be applied to the design of
low-level image processing algorithms. First, we show
how we implemented the food foraging application using
the EASEA software package. We then use this technique
to evolve an animat and learn how to move inside images
and detect high-gradient lines with a minimum
exploration time. The resulting animats do not use
standard {"}scanning + filtering{"} techniques but
develop other image exploration strategies close to
contour tracking. Experimental results on grey level
images are presented.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {Lake Como, Italy},
author = {Bolis, Enzo and Zerbi, Christian and Collet, Pierre and Louchet, Jean and Lutton, Evelyne},
biburl = {https://www.bibsonomy.org/bibtex/270da01ee1a8c53d648f74a63b31466cf/brazovayeye},
booktitle = {Genetic Programming, Proceedings of EuroGP'2001},
editor = {Miller, Julian F. and Tomassini, Marco and Lanzi, Pier Luca and Ryan, Conor and Tettamanzi, Andrea G. B. and Langdon, William B.},
interhash = {f0263e64b9c38b946cff13db61ce1404},
intrahash = {70da01ee1a8c53d648f74a63b31466cf},
isbn = {3-540-41899-7},
keywords = {Animat Contour EASEA, Image algorithms, detection, genetic processing, programming,},
month = {18-20 April},
notes = {EuroGP'2001, part of \cite{miller:2001:gp}},
organisation = {EvoNET},
pages = {246--255},
publisher = {Springer-Verlag},
publisher_address = {Berlin},
series = {LNCS},
size = {10 pages},
timestamp = {2008-06-19T17:36:44.000+0200},
title = {A {GP} Artificial Ant for image processing:
preliminary experiments with {EASEA}},
url = {http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=246},
volume = 2038,
year = 2001
}