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		<identifier>8JMKD3MGPBW34M/38737C8</identifier>
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		<site>sibgrapi.sid.inpe.br 802</site>
		<citationkey>AlvesHash:2010:TeReEx</citationkey>
		<author>Alves, Wonder Alexandre Luz,</author>
		<author>Hashimoto, Ronaldo Fumio,</author>
		<affiliation>Institute of Mathematics and Statistics - University of São Paulo</affiliation>
		<affiliation>Institute of Mathematics and Statistics - University of São Paulo</affiliation>
		<title>Text Regions Extracted from Scene Images by Ultimate Attribute Opening and Decision Tree Classification</title>
		<conferencename>Conference on Graphics, Patterns and Images, 23 (SIBGRAPI)</conferencename>
		<year>2010</year>
		<editor>Bellon, Olga,</editor>
		<editor>Esperança, Claudio,</editor>
		<booktitle>Proceedings</booktitle>
		<date>Aug. 30 - Sep. 3, 2010</date>
		<publisheraddress>Los Alamitos</publisheraddress>
		<publisher>IEEE Computer Society</publisher>
		<conferencelocation>Gramado</conferencelocation>
		<keywords>scene-text localization, connected component approach, text   information extraction, residual operator.</keywords>
		<abstract>In this work we propose a method for localizing text regions within scene images consisting of two major stages.  In the first stage, a set of potential text regions is extracted from the input image using residual operators (such as ultimate attribute opening and closing). In the second stage a set of features is obtained from each potential text region and this feature set will be later used as an input to a decision tree classifier in order to label these regions as text or non-text regions. Experiments performed using images from ICDAR public dataset show that this method is a good alternative for problems involving text location in scene images.</abstract>
		<language>en</language>
		<tertiarytype>Full Paper</tertiarytype>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi/2010/09.02.12.19</url>
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