A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture
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 c...
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| Format: | Article |
| Language: | English |
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Wiley
2011-01-01
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| Series: | International Journal of Reconfigurable Computing |
| Online Access: | http://dx.doi.org/10.1155/2011/712494 |
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| _version_ | 1850219143540768768 |
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| author | Emerson Carlos Pedrino José Hiroki Saito Valentin Obac Roda |
| author_facet | Emerson Carlos Pedrino José Hiroki Saito Valentin Obac Roda |
| author_sort | Emerson Carlos Pedrino |
| collection | DOAJ |
| description | 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 color image practical applications using the developed architecture are presented and the results are compared with similar techniques found in the literature. |
| format | Article |
| id | doaj-art-784faa73caf741a19fefe18008587523 |
| institution | OA Journals |
| issn | 1687-7195 1687-7209 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Reconfigurable Computing |
| spelling | doaj-art-784faa73caf741a19fefe180085875232025-08-20T02:07:28ZengWileyInternational Journal of Reconfigurable Computing1687-71951687-72092011-01-01201110.1155/2011/712494712494A Genetic Programming Approach to Reconfigure a Morphological Image Processing ArchitectureEmerson Carlos Pedrino0José Hiroki Saito1Valentin Obac Roda2Computer Science Department, Federal University of São Carlos, Rodovia Washington Luís, km 235, 13565-905 São Carlos, SP, BrazilComputer Science Department, Federal University of São Carlos, Rodovia Washington Luís, km 235, 13565-905 São Carlos, SP, BrazilDepartment of Electrical Engineering, University of São Paulo, Avenida Trabalhador São Carlense, 400 13566-590 São Carlos SP, BrazilMathematical 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 color image practical applications using the developed architecture are presented and the results are compared with similar techniques found in the literature.http://dx.doi.org/10.1155/2011/712494 |
| spellingShingle | Emerson Carlos Pedrino José Hiroki Saito Valentin Obac Roda A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture International Journal of Reconfigurable Computing |
| title | A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture |
| title_full | A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture |
| title_fullStr | A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture |
| title_full_unstemmed | A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture |
| title_short | A Genetic Programming Approach to Reconfigure a Morphological Image Processing Architecture |
| title_sort | genetic programming approach to reconfigure a morphological image processing architecture |
| url | http://dx.doi.org/10.1155/2011/712494 |
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