Improved AFIS for Color and Gray Image based on Biometric Triangulation

Authors

  • María del Carmen Espino-Gudiño Facultad de Ingeniería, Universidad Autónoma de Querétaro, Centro Universitario, Cerro de las Campanas, C.P. 76010, Querétaro, México.
  • Vicente Rodríguez-Hernández Facultad de Ingeniería e Informática, Universidad Autónoma de Q uerétaro, Centro Universitario, Cerro de las Campanas, C.P. 76010, Querétaro, México.
  • Iván R. Terol Villalobos CIDETEQ, Parque Tecnológico Querétaro S/N, San Fandila-Pedro E scobedo, C.P. 76700, Querétaro, México.
  • Gilberto Herrera Ruiz Facultad de Ingeniería, Universidad Autónoma de Querétaro, Centro Universitario, Cerro de las Campanas, C.P. 76010, Querétaro, México.

Keywords:

AFIS, Biometric patterns, Minutiae, Color and gray fingerprints, Image processing

Abstract

This research presents a fingerprint image processing algorithm for personal automatic identification, which has been in development since 1998. It is principally based on the comparison of the fingerprint's biometric pattern between the fingerprint captured (original) in each session and the one stored in database. It is preferable to capture the image in color. The biometric pattern is formed by the Euclidean distances based on the triangulation of only three minutiae. This methodology locates the position and the type of each minutia to perform the triangulation. The applied metric is the statistic similarity obtained by the comparison of both biometric patterns. This technique enables one to solve translation and rotation problems. An original colored fingerprint is used in order to obtain more information about the fingerprint situation. The space color used is HCL, because it helps get a good skin color for an encrypt key, which is formed by each channel (HCL) in accordance with the skin color. This system has several applications due to its low cost and efficiency. Finally, the results obtained with this methodology were satisfactory since in all the experimental tests the system offered a rate of global success of 99 %.

Downloads

Download data is not yet available.

References

[1] Allan Hanbury and Jean Serra. A 3D polar Coordinate Colour Representation Suitable for Image Analysis, Pattern recognition and Image Processing Group. PRIP-TR-77. 2005.
[2] Andrew K. Hrechack and James A. McHugh. Automated fingerprint recognition using structural matching, 23 (8): 893-904, 1990.
[3] Cédric Neumann, Christophe Champod, Roberto Puch-Solis, Nicole Egli, Alexandre Anthonioz ad Andie Bromage-Grffiths. Coputation of likelihood ratios in fingerprint identification for configurations of any number of minutiae. Journal Forensic Sci, Vol, 52, No, 1, 2007.
[4] Charles E. H. Berger, Jan A. de Koeijer, Wendy Glas,Henk T. Madhuizen, Color separation in forensic image processing. Journal of Forensic Sciences 51(1),100-102,2006.
[5] Chen Qin-Sheng, Defrise M, and Deconick F. Symetric phase only matched filtering of Fourier Mellin transforms for imagen registration and recognition. Pttern Anaysis Machine Intelligence IEEE, 16 (12): 1156-1168. 1994
[6] Daravall G. Allende. Reconocimiento de formas y visión artificial, Addisson Wesley, Madrid España., 1993.
[7] David C. Hitchcock. Thesis, Evaluation and combination of biometric authentication systems, University of Florida. 2003.
[8] Edba L. F. A fast thinning algorithm for character, Engenharia Electrica UFU, Brasil. 1997
[9] Fernando Alonso-Fernandez, Julian Fierrez-Aguilar and Javier Ortega-Garcia. A review of schemes for fingerprint image quality computation biometrics relab.- ATVS, Escuela Politecnica Superior - Universidad Autonoma de Madrid. Third COST 275 Workshop. Biometrics on the Internet by University of Hertfordshire Hatfield, UK, pp 3-6, 27-28 October 2005.
[10] Germaín Cárdenas and Guillermo Kemper. Sistema de reconocimiento de huellas dactilares, Universidad Peruana de ciencias aplicadas, 1-4, 2002.
[11] Gregory A. Baxes. Digital imege processing, principles and applications. John Wiley – Sons, Inc. 1994
[12] Haim Levkowits and Gabor T. Herman. A generalized lightness, hue and saturation color model. CVGIP: Graphical Models and Image Processing, 55(4): 271’285, 1993.
[13] Jesús Angulo. Morphological color processing based on distances application to color denoising and enhacement by centre and contrast operators. Centre de Morphologie Mathématique- Ecole des Mines de Paris., 2005.
[14] José A. Domínguez, Thesis, Fourier based methods in CAD, Cranfield Institution of technology, 1. 1995.
[15] Juan Serrat, A. López and D. Lloret. On ridges and valleys. Pattern Recognition Internatiional Conference (15th), 2000.
[16] Julian Ashbourn. Biometrics advanced identity verification, the complete guide. Springer Verlag London, 2002.
[17] Kenneth R. Castleman. Digital image processing, Pretice Hall, 1996.
[18] Lin Hong and Anil K. Jain. Classification of fingerprint images, Kangerlussuaq, Greenland, Proceedings of 11th Scandinavian conference on image analysis, 7-11. 1999.
[19] Ma del Carmen Espino-Gudiño., I. Santillan, Iván R. Terol-Villalobos. Morphological multiscale contrast approach for gray and color images consistent with human visual perception, Optical Engineering 46 (6), 1-14. 2007.
[20] Martín Drahanský. Biometric security systems fingerprint recognition technology, Brn University of Techology, departament of intelligent system. 2005.
[21] N. K. Ratha, K. Karu, S. Chen and A. K. Jain. A real-time matching system for large fingerprint databases, IEEE TPAMI 18(8): 799, 1996.
[22] Neil Yager and Adnan Amin. Coarse fingerprint registration using orientation fields, EURASIP Journal on applied signal processing, 13:2043-2053, 2005.
[23] Rafael C. Gonzalez and Richard E. Woods. Digital image processing, Addison Wesley. 2002.
[24] Sarifuddin M. and Missaoui R. A new perceptually uniform color space with associated color similarity measure for content-based image and video retrieval. Département d’informatique et d’ingénierie, Université du Québec en Outaouais, Québec Canada, J8X 3X7. pp 1-8, 2005.
[25] Simon A. Cole. Is fingerprint identification valid? rhetorics of reliability in fingerprint proponents discourse, Baldy Center for law and social policy and Blackwell publishing Ltd. 28(1):109-132, 2006.
[26] Ted G. Software Fastgraph for windows, 1995.
[27] Vicente Rodríguez-Hernández. Procesamiento de Huellas Dactilares. Tesis de Maestría en Ciencias de laComputación, Fundación Arturo Rosenblueth, 1998.
[28] Víctor E. A. Pérez and Manuel I. M. Ortiz. Reconocimiento de huellas digitales en escala de grises, Facultad de ciencias de la computación, Benemérita Universidad Autónoma de Puebla, 2005.
[29] Yin Yilong, Tian Jie and Yang Xiukun. Ridge distance estimation in fingerprint images: Algorithm and performance evaluation, EURASIP Journal on applied signal processing, 4:495-502, 2004.

Downloads

Published

2007-10-01

How to Cite

Espino-Gudiño, M. del C., Rodríguez-Hernández, V., Terol Villalobos, I. R., & Herrera Ruiz, G. (2007). Improved AFIS for Color and Gray Image based on Biometric Triangulation. Journal of Computer Science and Technology, 7(03), p. 228–234. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/775

Issue

Section

Original Articles