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		<identifier>8JMKD3MGPBW4/35S6242</identifier>
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		<doi>10.1109/SIBGRAPI.2009.22</doi>
		<citationkey>KomatiSallSarc:2009:JSUsHo</citationkey>
		<title>Fractal-JSEG: JSEG Using an Homogeneity Measurement Based on Local Fractal Descriptor</title>
		<format>Printed, On-line.</format>
		<year>2009</year>
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		<author>Komati, Karin Satie,</author>
		<author>Salles, Evandro Ottoni Teatini,</author>
		<author>Sarcinelli-Filho, Mario,</author>
		<affiliation>Federal University of Espirito Santo</affiliation>
		<affiliation>Federal University of Espirito Santo</affiliation>
		<affiliation>Federal University of Espirito Santo</affiliation>
		<editor>Nonato, Luis Gustavo,</editor>
		<editor>Scharcanski, Jacob,</editor>
		<e-mailaddress>kkomati@ele.ufes.br</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI)</conferencename>
		<conferencelocation>Rio de Janeiro, RJ, Brazil</conferencelocation>
		<date>11-14 Oct. 2009</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>color image segmentation, J value segmentation (JSEG), edge detection, fractal dimension, local fractal operator, differential box-counting (DBC).</keywords>
		<abstract>This paper proposes an improved version for the JSEG color image segmentation algorithm, combining the classical JSEG algorithm and a local fractal operator that measures the fractal dimension of each pixel, thus improving the boundary detection in the J-map. Experiments with natural color images of the Berkeley Segmentation Dataset and Benchmark are presented, which show improved results in comparison with the classical JSEG algorithm.</abstract>
		<language>en</language>
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		<usergroup>kkomati@ele.ufes.br</usergroup>
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