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@InProceedings{RodriguesBorg:2018:EsCoSo,
               author = "Rodrigues, Emily S. and Borges, Vinicius R. P.",
          affiliation = "{Universidade de Bras{\'{\i}}lia} and {Universidade de 
                         Bras{\'{\i}}lia}",
                title = "Estudo comparativo sobre o uso de pr{\'e}-processamento na 
                         detec{\c{c}}{\~a}o de poros de suor em impress{\~o}es 
                         digitais",
            booktitle = "Proceedings...",
                 year = "2018",
               editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and 
                         Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and 
                         Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez, 
                         Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de 
                         and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa, 
                         Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus, 
                         Klaus de and Scheer, Sergio",
         organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "biometria, impress{\~a}o digital, poros de suor, processamento de 
                         imagem, pr{\'e}-processamento.",
             abstract = "This paper describes a study regarding the use of image 
                         preprocessing techniques to improve the quality of fingerprints in 
                         digital images. We investigated and compared some low-pass 
                         filtering (Gaussian, median and anisotropic diffusion filtering) 
                         and contrast enhancement (histogram equalization and image 
                         normalization) techniques for identifying and extracting pores in 
                         high resolution images. Our study was conducted by using an 
                         automatic methodology for pore extraction in high resolution 
                         fingerprint images, in which we considered several combinations of 
                         filtering and contrast enhancement methods. Experiments were 
                         performed using a public fingerprint image set and compared the 
                         true pore and false pore detection rates of those combinations in 
                         relation to the ground-truth images. The results reported that the 
                         combination image normalization alongside anisotropic diffusion 
                         filtering yielded the best performance.",
  conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
      conference-year = "Oct. 29 - Nov. 1, 2018",
             language = "pt",
                  ibi = "8JMKD3MGPAW/3S4TFL5",
                  url = "http://urlib.net/rep/8JMKD3MGPAW/3S4TFL5",
           targetfile = "SIBGRAPI2018.pdf",
        urlaccessdate = "2020, Aug. 06"
}


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