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		<isbn>978-85-7669-273-7</isbn>
		<citationkey>MoreiraCost:1995:MuImSe</citationkey>
		<title>Multispectral image segmentation by chromaticity classification</title>
		<format>Impresso, On-line.</format>
		<year>1995</year>
		<numberoffiles>1</numberoffiles>
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		<author>Moreira, Jander,</author>
		<author>Costa, Luciano da Fontoura,</author>
		<affiliation>Departamento de Computação da Universidade de São Carlos (UFSCar)</affiliation>
		<affiliation>Instituto de Física de São Carlos (IFSC) da Universidade de São Paulo (USP)</affiliation>
		<editor>Lotufo, Roberto de Alencar,</editor>
		<editor>Mascarenhas, Nelson Delfino d'Ávila,</editor>
		<e-mailaddress>cintiagraziele.silva@gmail.com</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 8 (SIBGRAPI)</conferencename>
		<conferencelocation>São Carlos, SP, Brazil</conferencelocation>
		<date>25-27 Oct. 1995</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<pages>119-125</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigo</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>image segmentation, multispectral image segmentation, chromaticity classification.</keywords>
		<abstract>This paper describes a color segmentation technique, based on the k-nearest-neighbor classification scheme, which operates on a normalized version of the color image known as the chromaticity image. An investigation was carried out in order to evaluate how the classification behaves for different number of neighbors (k), for distinct window sizes (in which an average of a sample feature is taken), and for various numbers of samples per class. The results, which are experimentally assessed by comparing the obtained classifications with a standard reference (segmented by human), shows that the method provides good overall accuracy and robustness. The class space for the test image is also presented in graphical form.</abstract>
		<type>Segmentação de Imagens</type>
		<language>en</language>
		<targetfile>15 Multispectral image.pdf</targetfile>
		<usergroup>cintiagraziele.silva@gmail.com</usergroup>
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