Detalhes bibliográficos
Ano de defesa: |
2007 |
Autor(a) principal: |
Laprano, Cassius Mazzo |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Não Informado pela instituição
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
|
Link de acesso: |
http://www.repositorio.ufc.br/handle/riufc/16062
|
Resumo: |
This dissertation deals with the localization of Brazilian license plates of private vehicles, and recognition of their characters. Images of moving cars, acquired by diverse analog systems of traffic law enforcement were used to test the algorithms. These images were digitalized by a scanner and finally formatted as JPG or JPEG (Joint Photographic Experts Group). The proposed system is classified as a vehicle license plate recognition system(VLPRS), whose purpose is the traffic law enforcement. The system is able to identify license plate numbers of drivers who jump red lights and exceed the speed limit. Several algorithms which constitute the overall system were evaluated and compared with the performance of similar ones from the literature. The main contributions of this work are: the localization plate algorithm, based on a neural network; the use of the Min/Max algorithm to post processing binary images, and the use of the method of rows and columns in the characters isolation step. To assess the system performance some tests were provided using the two proposed methods for plate localization which are based on the maximum correlation and a feedforward neural network. We concluded that the latter performed better than the former according to the simulation results obtained for the set of images used. |