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		<isbn>85-244-0103-6</isbn>
		<citationkey>CandeasBragCarv:1996:MaMoAp</citationkey>
		<title>A mathematical morphology approach to the characterization of astronomical objects</title>
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		<year>1996</year>
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		<author>Candeas, Alcione Jandir,</author>
		<author>Braga Neto, Ulisses de Mendonça,</author>
		<author>Carvalho Filho, Edson Costa de Barros,</author>
		<editor>Velho, Luiz,</editor>
		<editor>Albuquerque, Arnaldo de,</editor>
		<editor>Lotufo, Roberto A.,</editor>
		<conferencename>Simpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 9 (SIBGRAPI)</conferencename>
		<conferencelocation>Caxambu, MG, Brazil</conferencelocation>
		<date>29 Oct.-1 Nov. 1996</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<pages>235-242</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigo</tertiarytype>
		<organization>SBC - Sociedade Brasileira de Computação; UFMG - Universidade Federal de Minas Gerais</organization>
		<transferableflag>1</transferableflag>
		<abstract>We deal in this work with a broadly studied topic in astronomical imaging, namely the star/galaxy discrimination problem. Through the use of Mathematical Morphology, we propose an original approach to the characterization of these astronomical objects, which is based on gray-level shape information. The main steps in our method are image pre-processing, segmentation and feature extraction, all of which employ Mathematical Morphology tools that were implemented using the MMach toolbox for the Khoros system. We present a comparison between our segmentation results, based on the watershed method, and those of a classical software package SExtractor. The shape information is extracted through the use of the gray-level morphological pattern spectrum, which yields very satisfactory shape features, that promise to be very suitable for future work in neural-network automatic classification.</abstract>
		<type>Morfologia Matemática</type>
		<language>en</language>
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