Algoritmo genético embarcado aplicado à indução de operadores morfológicos
| Main Author: | |
|---|---|
| Publication Date: | 2016 |
| Format: | Master thesis |
| Language: | por |
| Source: | Repositório Institucional da UFSCAR |
| Download full: | https://repositorio.ufscar.br/handle/20.500.14289/12096 |
Summary: | The use of genetic algorithms, evolutionary strategies and genetic programming has been notoriously addressed in the areas of image processing and computer vision and has contributed with diverse results. However, this approach requires large computing power. Some academic papers bring these algorithms for the areas of embedded and dedicated systems, improving in this way the performance of algorithms and minimizing the computational cost. This design addresses the implementation of these algorithms applied to morphological processing of images using FPGAs and Verilog-HDL. The genetic algorithm is adapted for a more intuitive and simple implementation for the development of a dedicated hardware and it may contribute to reduce logical resources and enhance performece. Studies and tests carried out during the project showed good results for the proposed design. |
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Tognoli, Éttore LeandroPedrino, Emerson Carloshttp://lattes.cnpq.br/6481363465527189http://lattes.cnpq.br/156362870192836540b11319-6e00-4263-b7c8-8043e5befb012019-12-03T13:44:29Z2019-12-03T13:44:29Z2016-03-07TOGNOLI, Éttore Leandro. Algoritmo genético embarcado aplicado à indução de operadores morfológicos. 2016. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/20.500.14289/12096.https://repositorio.ufscar.br/handle/20.500.14289/12096The use of genetic algorithms, evolutionary strategies and genetic programming has been notoriously addressed in the areas of image processing and computer vision and has contributed with diverse results. However, this approach requires large computing power. Some academic papers bring these algorithms for the areas of embedded and dedicated systems, improving in this way the performance of algorithms and minimizing the computational cost. This design addresses the implementation of these algorithms applied to morphological processing of images using FPGAs and Verilog-HDL. The genetic algorithm is adapted for a more intuitive and simple implementation for the development of a dedicated hardware and it may contribute to reduce logical resources and enhance performece. Studies and tests carried out during the project showed good results for the proposed design.A utilização de algoritmos genéticos, estratégias evolutivas e programação genética tem sido notoriamente abordada nas áreas de processamento de imagens e visão computacional e tem contribuído com resultados diversificados. Entretanto, esse tipo de abordagem necessita de grande poder computacional para que o tempo de processamento seja viável. Alguns trabalhos acadêmicos trazem esses algoritmos para as áreas de sistemas embarcados e dedicados, melhorando dessa forma, o desempenho dos algoritmos e minimizando o custo computacional. Este projeto aborda a implementação de um desses algoritmos, aplicado ao processamento morfológico de imagens, utilizando FPGAs e Verilog-HDL. O algoritmo genético desenvolvido é adaptado a uma implementação mais intuitiva e simples para o desenvolvimento de um hardware dedicado, podendo contribuir no desempenho do sistema, reduzir o tempo de treinamento e reduzir o consumo de recursos lógicos. Os estudos e testes realizados durante o projeto demonstraram bons resultados para a adaptação proposta.Não recebi financiamentoporUniversidade Federal de São CarlosCâmpus São CarlosPrograma de Pós-Graduação em Ciência da Computação - PPGCCUFSCarAttribution 3.0 Brazilhttp://creativecommons.org/licenses/by/3.0/br/info:eu-repo/semantics/openAccessAlgoritmo genéticoFPGAMorfologia matemáticaSistema embarcadoProcessamento de imagenshardwareGenetic algorithmMathematical morphologyEmbedded systemimage processingCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAOAlgoritmo genético embarcado aplicado à indução de operadores morfológicosEmbedded genetic algorithm applied on mathematical morphology operators inductioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisOnline6006008f641ac4-ef66-4fde-b5d9-8a5e4cfacc8areponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARLICENSElicense.txtlicense.txttext/plain; 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| dc.title.por.fl_str_mv |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| dc.title.alternative.eng.fl_str_mv |
Embedded genetic algorithm applied on mathematical morphology operators induction |
| title |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| spellingShingle |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos Tognoli, Éttore Leandro Algoritmo genético FPGA Morfologia matemática Sistema embarcado Processamento de imagens hardware Genetic algorithm Mathematical morphology Embedded system image processing CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO |
| title_short |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| title_full |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| title_fullStr |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| title_full_unstemmed |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| title_sort |
Algoritmo genético embarcado aplicado à indução de operadores morfológicos |
| author |
Tognoli, Éttore Leandro |
| author_facet |
Tognoli, Éttore Leandro |
| author_role |
author |
| dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/1563628701928365 |
| dc.contributor.author.fl_str_mv |
Tognoli, Éttore Leandro |
| dc.contributor.advisor1.fl_str_mv |
Pedrino, Emerson Carlos |
| dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/6481363465527189 |
| dc.contributor.authorID.fl_str_mv |
40b11319-6e00-4263-b7c8-8043e5befb01 |
| contributor_str_mv |
Pedrino, Emerson Carlos |
| dc.subject.por.fl_str_mv |
Algoritmo genético FPGA Morfologia matemática Sistema embarcado Processamento de imagens |
| topic |
Algoritmo genético FPGA Morfologia matemática Sistema embarcado Processamento de imagens hardware Genetic algorithm Mathematical morphology Embedded system image processing CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO |
| dc.subject.eng.fl_str_mv |
hardware Genetic algorithm Mathematical morphology Embedded system image processing |
| dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO |
| description |
The use of genetic algorithms, evolutionary strategies and genetic programming has been notoriously addressed in the areas of image processing and computer vision and has contributed with diverse results. However, this approach requires large computing power. Some academic papers bring these algorithms for the areas of embedded and dedicated systems, improving in this way the performance of algorithms and minimizing the computational cost. This design addresses the implementation of these algorithms applied to morphological processing of images using FPGAs and Verilog-HDL. The genetic algorithm is adapted for a more intuitive and simple implementation for the development of a dedicated hardware and it may contribute to reduce logical resources and enhance performece. Studies and tests carried out during the project showed good results for the proposed design. |
| publishDate |
2016 |
| dc.date.issued.fl_str_mv |
2016-03-07 |
| dc.date.accessioned.fl_str_mv |
2019-12-03T13:44:29Z |
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2019-12-03T13:44:29Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
| dc.identifier.citation.fl_str_mv |
TOGNOLI, Éttore Leandro. Algoritmo genético embarcado aplicado à indução de operadores morfológicos. 2016. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/20.500.14289/12096. |
| dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/20.500.14289/12096 |
| identifier_str_mv |
TOGNOLI, Éttore Leandro. Algoritmo genético embarcado aplicado à indução de operadores morfológicos. 2016. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/20.500.14289/12096. |
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por |
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por |
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openAccess |
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Universidade Federal de São Carlos Câmpus São Carlos |
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Programa de Pós-Graduação em Ciência da Computação - PPGCC |
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Universidade Federal de São Carlos Câmpus São Carlos |
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