Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2002: administrator
Metadata Last Update2020: administrator
Citation KeyJustinoYacoBortSabo:2000:OfSiVe
TitleAn off-line signature verification system using hidden Markov model and cross-validation
Access Date2021, Jan. 19
Number of Files1
Size494 KiB
Context area
Author1 Justino, Edson J. R.
2 Yacoubi, Abdenaim El
3 Bortolozzi, Flávio
4 Sabourin, Robert
EditorCarvalho, Paulo Cezar Pinto
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History2008-07-17 14:10:49 :: administrator -> banon ::
2008-08-26 15:23:01 :: banon -> administrator ::
2009-08-13 20:36:54 :: administrator -> banon ::
2010-08-28 20:00:09 :: banon -> administrator ::
2020-02-19 02:58:51 :: administrator -> :: 2000
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordshandwriting 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.
AbstractThe 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.
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Notes area
NotesThe conference was held in Gramado, RS, Brazil, from October 17 to 20.
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