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		<doi>10.1109/SIBGRAPI.2001.963038</doi>
		<citationkey>BrunBaHiTrDaTe:2001:MuClTr</citationkey>
		<title>Multi-resolution classification trees in OCR design</title>
		<year>2001</year>
		<numberoffiles>1</numberoffiles>
		<size>660 KiB</size>
		<author>Brun, Marcel,</author>
		<author>Barrera, Junior,</author>
		<author>Hirata, Nina S. T.,</author>
		<author>Trepode, Nestor W.,</author>
		<author>Dantas, Daniel,</author>
		<author>Terada, Routo,</author>
		<editor>Borges, Leandro Díbio,</editor>
		<editor>Wu, Shin-Ting,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 14 (SIBGRAPI)</conferencename>
		<conferencelocation>Florianópolis, SC, Brazil</conferencelocation>
		<date>15-18 Oct. 2001</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<pages>59-66</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>classification trees, OCR, morphological multi-classifier.</keywords>
		<abstract>This paper recalls the idea of classification trees in OCR (Optical Character Recognition) systems and proposes a technique for the automatic design of these classification trees. The design of both the classification trees and of the classification operators are based on training from sample pairs of observed-ideal images, allowing the development of customized OCRs.</abstract>
		<language>en</language>
		<targetfile>59-66.pdf</targetfile>
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		<notes>The conference was held in Florianópolis, SC, Brazil, from October 15 to 18.</notes>
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