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@InProceedings{SáLotu:2006:ImFiMa,
               author = "de S{\'a}, Gustavo Ferreira Cradoso and Lotufo, Roberto de 
                         Alencar",
          affiliation = "{Universidade Estadual de Campinas} and {Unversidade Estadual de 
                         Campinas}",
                title = "Improved FingerCode Matching Function",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Oliveira Neto, Manuel Menezes de and Carceroni, Rodrigo Lima",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 19. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Fingerprint, FingerCode.",
             abstract = "FingerCode is a fingerprint correlation matching scheme that 
                         relies on texture information. In this scheme, the oriented 
                         components are extracted from a fingerprint image using a bank of 
                         Gabor filters, and a directional texture feature vector is 
                         computed for each oriented component. The feature vectors from the 
                         input and template images are compared and a matching score is 
                         obtained. Here we explore ways to improve the matching score for 
                         the FingerCode method by using more complex matching functions. 
                         The best results were obtained by applying a nonlinear function to 
                         the texture values and weighting the texture vectors based on the 
                         spatial distribution.",
  conference-location = "Manaus",
      conference-year = "8-11 Oct. 2006",
             language = "en",
           targetfile = "PID282231.pdf",
        urlaccessdate = "2020, Nov. 25"
}


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