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		<doi>10.1109/SIBGRA.2000.883926</doi>
		<citationkey>FloresHirBarLotMey:2000:MoOpSe</citationkey>
		<title>Morphological operators for segmentation of color sequences</title>
		<year>2000</year>
		<numberoffiles>1</numberoffiles>
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		<author>Flores, Franklin César,</author>
		<author>Hirata Jr., Roberto,</author>
		<author>Barrera, Junior,</author>
		<author>Lotufo, Roberto A.,</author>
		<author>Meyer, Fernand,</author>
		<editor>Carvalho, Paulo Cezar Pinto,</editor>
		<editor>Walter, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)</conferencename>
		<conferencelocation>Gramado, RS, Brazil</conferencelocation>
		<date>17-20 Oct. 2000</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<pages>300-307</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>mathematical morphology, morphological operators, color sequence segmentation, moving object segmentation, image sequences, computational learning, statistical optimization, video frames, mathematical morphology.</keywords>
		<abstract>This paper presents a technique for the segmentation of moving objects in color image sequences. The technique is based on Beucher-Meyer paradigm, with markers detected by a morphological operator designed by computational learning (or, equivalently, statistical optimization). Objects in some frames of the video are marked manually and used to train the markers detector. Then, the operator designed is used to mark the objects in the other frames and the paradigm is applied to all frames marked by the detector. Two real world examples illustrate the application of the proposed technique.</abstract>
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		<notes>The conference was held in Gramado, RS, Brazil, from October 17 to 20.</notes>
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