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		<citationkey>AlmeidaVascBeni:2015:FrDeSe</citationkey>
		<title>Framework para Detecção de Semáforos Baseado em Atenção Visual</title>
		<format>On-line</format>
		<year>2015</year>
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		<author>Almeida, Thiago,</author>
		<author>Vasconcelos, Nathanael,</author>
		<author>Benicasa, Alcides,</author>
		<affiliation>Universidade Federal de Sergipe</affiliation>
		<affiliation>Universidade Federal de Sergipe</affiliation>
		<affiliation>Universidade Federal de Sergipe</affiliation>
		<editor>Vieira, Thales Miranda de Almeida,</editor>
		<editor>Mello, Vinicius Moreira,</editor>
		<e-mailaddress>thiago7a@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 28 (SIBGRAPI)</conferencename>
		<conferencelocation>Salvador</conferencelocation>
		<date>Aug. 26-29, 2015</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Undergraduate Work</tertiarytype>
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		<keywords>-chave-detecção e reconhecimento de semáforo, sistemas de transporte inteligentes, atenção visual, processamento de imagens, reconhecimento baseado em histograma de cores.</keywords>
		<abstract>This article aims to propose a detection and recognition mechanism of traffic lights which is based on biological concepts of artificial intelligence, specifically visual attention, and image processing. The proposed mechanism uses information from the color histogram of the detected area for classifying scene as having a red or green light. Experimental results obtained in the daytime and nighttime periods reveal the efficiency of the proposed framework.</abstract>
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