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@InProceedings{JustinoYacoBortSabo:2000:OfSiVe,
               author = "Justino, Edson J. R. and Yacoubi, Abdenaim El and Bortolozzi, 
                         Fl{\'a}vio and Sabourin, Robert",
                title = "An off-line signature verification system using hidden Markov 
                         model and cross-validation",
                 year = "2000",
               editor = "Carvalho, Paulo Cezar Pinto and Walter, Marcelo",
                pages = "105--112",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 13. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
                 note = "The conference was held in Gramado, RS, Brazil, from October 17 to 
                         20.",
             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.",
             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.",
  conference-location = "Gramado, RS, Brazil",
      conference-year = "October",
         organisation = "SBC - Brazilian Computer Society",
           targetfile = "105-112.pdf",
        urlaccessdate = "2020, Nov. 29"
}


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