A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture
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- @Article{Pedrino:2011:IJRC,
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author = "Emerson Carlos Pedrino and Jose Hiroki Saito and
Valentin Obac Roda",
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title = "A Genetic Programming Approach to Reconfigure a
Morphological Image Processing Architecture",
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journal = "International Journal of Reconfigurable Computing",
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year = "2011",
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volume = "2011",
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number = "Article ID 712494",
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keywords = "genetic algorithms, genetic programming",
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publisher = "Hindawi Publishing Corporation",
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ISSN = "16877195",
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bibsource = "OAI-PMH server at www.doaj.org",
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language = "eng",
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oai = "oai:doaj-articles:eed67a745bb9ae9d853b26e9682e4311",
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URL = "http://downloads.hindawi.com/journals/ijrc/2011/712494.pdf",
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DOI = "doi:10.1155/2011/712494",
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size = "10 pages",
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abstract = "Mathematical morphology supplies powerful tools for
low-level image analysis. Many applications in computer
vision require dedicated hardware for real-time
execution. The design of morphological operators for a
given application is not a trivial one. Genetic
programming is a branch of evolutionary computing, and
it is consolidating as a promising method for
applications of digital image processing. The main
objective of genetic programming is to discover how
computers can learn to solve problems without being
programmed for that. In this paper, the development of
an original reconfigurable architecture using logical,
arithmetic, and morphological instructions generated
automatically by a genetic programming approach is
presented. The developed architecture is based on FPGAs
and has among the possible applications, automatic
image filtering, pattern recognition and emulation of
unknown filter. Binary, gray, and colour image
practical applications using the developed architecture
are presented and the results are compared with similar
techniques found in the literature.",
- }
Genetic Programming entries for
Emerson Carlos Pedrino
Jose Hiroki Saito
Valentin Obac Roda
Citations