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		<citationkey>CostaBellSilv:2016:BiId3D</citationkey>
		<title>Biometric Identification with 3D Fingerprints Acquired Through Optical Coherence Tomography</title>
		<format>On-line</format>
		<year>2016</year>
		<numberoffiles>1</numberoffiles>
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		<author>Costa, Henrique Sérgio Gutierrez da,</author>
		<author>Bellon, Olga Regina Pereira,</author>
		<author>Silva, Luciano,</author>
		<affiliation>Universidade Federal do Paraná</affiliation>
		<affiliation>Universidade Federal do Paraná</affiliation>
		<affiliation>Universidade Federal do Paraná</affiliation>
		<editor>Aliaga, Daniel G.,</editor>
		<editor>Davis, Larry S.,</editor>
		<editor>Farias, Ricardo C.,</editor>
		<editor>Fernandes, Leandro A. F.,</editor>
		<editor>Gibson, Stuart J.,</editor>
		<editor>Giraldi, Gilson A.,</editor>
		<editor>Gois, João Paulo,</editor>
		<editor>Maciel, Anderson,</editor>
		<editor>Menotti, David,</editor>
		<editor>Miranda, Paulo A. V.,</editor>
		<editor>Musse, Soraia,</editor>
		<editor>Namikawa, Laercio,</editor>
		<editor>Pamplona, Mauricio,</editor>
		<editor>Papa, João Paulo,</editor>
		<editor>Santos, Jefersson dos,</editor>
		<editor>Schwartz, William Robson,</editor>
		<editor>Thomaz, Carlos E.,</editor>
		<e-mailaddress>hsgc1964@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)</conferencename>
		<conferencelocation>São José dos Campos, SP, Brazil</conferencelocation>
		<date>4-7 Oct. 2016</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Master's or Doctoral Work</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>3D Fingerprints, Biometric Identification, Optical Coherence Tomography.</keywords>
		<abstract>A method to obtain epidermal and dermal 3D fingerprints from high-resolution images acquired using Optical Coherence Tomography (OCT) is proposed. This method addresses limitations of current 3D reconstruction techniques such as depth and resolution variations, sensitivity to low illumination and poor contrast. The availability of these fingerprints made possible the creation of new identification techniques that benefit from the rich information available in 3D. We propose a 3D fingerprint matching process based on KH maps, which are 2D representations of curvature types extracted by computing the Gaussian and mean curvatures from a region of interest around minutiae.The matching strategy, a two-step approach, relies on local gradient patterns (LGP) of the KH maps to narrow the search space, followed by a similarity matching, normalized cross correlation. The accuracy and matching compatibility, comparable or improved in relation to the 2D matching methods, is verified through matching 3D fingerprints from two databases one acquired using OCT and a public database. An OCT 3D fingerprint database, the first acquired this technology to our knowledge, contains images of people of different ages, genders, ethnicity and cases of alterations as scars, abrasion and scratches. We investigate the applicability of our method to the identification of altered fingerprints. In these cases, the 3D dermal fingerprint, compatible with the epidermis, is employed.</abstract>
		<language>en</language>
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