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		<doi>10.1109/SIBGRA.2000.883902</doi>
		<citationkey>JustinoYacoBortSabo:2000:OfSiVe</citationkey>
		<title>An off-line signature verification system using hidden Markov model and cross-validation</title>
		<year>2000</year>
		<numberoffiles>1</numberoffiles>
		<size>494 KiB</size>
		<author>Justino, Edson J. R.,</author>
		<author>Yacoubi, Abdenaim El,</author>
		<author>Bortolozzi, Flávio,</author>
		<author>Sabourin, Robert,</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>105-112</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>handwriting recognition, off-line signature verification system, pre-processing process, segmentation process, feature extraction process, random falsifications, false acceptance concept, false rejection concept, hidden Markov model, cross-validation, learning process, intrapersonal variation, interpersonal variation, automatic decision threshold derivation.</keywords>
		<abstract>The main objective is to present an off-line signature verification system. It is basically divided into three parts. The first demonstrates a pre-processing process, a segmentation process and a feature extraction process, in which the main aim is to obtain the maximum performance quality of the process of verification of random falsifications, in the false acceptance and false rejection concept. The second presents a learning process based on HMM, where the aim is obtaining the best model. That is, one that is capable of representing each writer's signature, absorbing yet at the same time discriminating, at most the intrapersonal and interpersonal variation. The third presents a signature verification process that uses the models generated by the learning process without using any prior knowledge of test data, in other words, using an automatic derivation process of the decision thresholds.</abstract>
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		<notes>The conference was held in Gramado, RS, Brazil, from October 17 to 20.</notes>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2002/11.05.12.00</url>
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