SciELO - Scientific Electronic Library Online

 
vol.16 número3EditorialNuevo método analítico para calcular la impedancia característica Zc de líneas de transmisión uniformes índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Computación y Sistemas

versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546

Comp. y Sist. vol.16 no.3 Ciudad de México Jul./Set. 2012

 

Artículo invitado

 

Avances en el reconocimiento del iris: perspectivas y oportunidades en la investigación de algoritmos biométricos

 

Advances in Iris Recognition: Perspectives and Opportunities of Research in Biometric Algorithms

 

Mireya Sarai García-Vázquez1 y Alejandro Álvaro Ramírez-Acosta2

 

1 Centro de Investigación y Desarrollo de Tecnología Digital (CITEDI-IPN), Avenida del Parque No.1310, Tijuana, B.C. 22510 México mgarciav@citedi.mx

2 MIRAL. R & D, 1047 Palm Garden, Imperial Beach, 91932 USA, ramacos10@hotmail.com

 

Artículo recibido el 23/07/2012;
aceptado el 29/08/2012.

 

Resumen

Los últimos seis años han sido testigos de importantes avances en la aplicación de sistemas biométricos usando el iris en los sistemas de seguridad civiles y militares. Lo fundamental de este progreso ha sido el desarrollo de nuevos algoritmos biométricos, capaces de producir una autentificación muy confiable de individuos sin tener interacción con éste. La mayoría de estos algoritmos biométricos incorporan el video-iris para representar mejor las propiedades espaciales y frecuenciales de la textura del iris, optimizando el desempeño de reconocimiento del iris. El objetivo de este artículo es proporcionar una visión general de las metodologías de reconocimiento del iris, haciendo énfasis en los algoritmos que forman parte de las recientes aplicaciones de reconocimiento del iris a distancia y en ambientes no controlados. Aunque el énfasis esta en las nuevas tendencias, también se cubren las metodologías tradicionales de reconocimiento del iris. Finalmente se presenta una discusión de las oportunidades para la investigación futura.

Palabras clave: Reconocimiento del iris, biometría, video-iris, algoritmos de reconocimiento, reconocimiento a distancia, ambientes no controlados.

 

Abstract

The last six years witnessed important advances ¡n applying iris based biometric systems for military and civil security purposes. The fundamental aspect of this progress ¡s the development of biometric algorithms able to produce high confidence personal identification without human interaction. The majority of such biometric algorithms use iris video as a better representaron of special properties and features of the iris texture thus optimizing its recognition process. The goal of this paper ¡s to present a general overview of iris recognition methods with particular emphasis on the algorithms used ¡n recent applications for distant iris recognition as well as iris recognition ¡n uncontrolled environments. Though special attention ¡s given to the latest tendencies, traditional iris recognition methods are also described. Finally, some future research opportunities are discussed.

Keywords. Iris recognition, biometrics, iris video, recognition algorithms, distant recognition, uncontrolled environments.

 

DESCARGAR ARTÍCULO EN FORMATO PDF

 

Agradecimiento

Esta investigación fue auspiciada por el proyecto SIP2012 del IPN.

 

Referencias

1. Bertillon, M.A. (1885). Anthropologie, La couleur de l'iris. Revue scientifique, (SER3,A22,T10), 65-73.         [ Links ]

2. Flom L., Safir A. Iris Recognitions System. U.S. Patent, No. 4,641,349, 1987. http://www.google.com/patents/US4641349        [ Links ]

3. Daugman, J.G. (1993). High confidence visual recognition of persons by a test of statistical independence. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11), 1148— 1161.         [ Links ]

4. Biometric Personal Identification System Based on Iris Analysis. United States Patent 5291560, 1994.         [ Links ]

5. International Biometric Group (2008). The Biometrics Market and Industry Report 2009-2014.         [ Links ]

6. Yun, Y.W. (s.f.). The '123' of Biometric Technology. Retrieved from http://www.cp.su.ac.th/~rawitat/teaching/forensicit06/coursefiles/files/biometric.pdf        [ Links ]

7. Xueyan, L. & Shuxu, G. (2008). The Fourth Biometric - Vein Recognition. In Peng-Yeng Yin (Ed.), Pattern Recognition Techniques, Technology and Applications, (537-546), InTech.         [ Links ]

8. Acuity Market Intelligence. (2009). The Future of Biometrics Market Analysis, Segmentation & Forecasts.         [ Links ]

9. Luis-García, R., Alberola-López, C, Aghzout, O., & Ruiz-Alzola, J. (2003). Biometric identification systems. Signal Processing, 83(12), 2539-2557.         [ Links ]

10. Tisse, C.-L. (2003). Contribution á la vérification biométrique de personnes par reconnaissance del'iris. Thése doctorat, Université des sciences et techniques de Montpellier 2, Montpellier, France.         [ Links ]

11. Daugman, J. (2004). How iris recognition works. IEEE Transactions on Circuits and Systems for Video Technology, 14(1), 21-30.         [ Links ]

12. Wildes, R. (2004). Iris recognition. In James L. Wayman , Añil K. Jain, Davide Maltoni, Dario Maio (Eds), Biometric Systems: Technology, Design and Performance Evaluation (63-95), London: Springer-Verlag.         [ Links ]

13. Bowyer, K.W., Hollingsworth, K., & Flynn, P.J. (2008). Image Understanding for Iris Biometrics: A Survey. Computer Vision and Image Understanding, 110(2), 281-307.         [ Links ]

14. Daugman, J. (2009). Iris Recognition at Airports and Border-Crossings. Encyclopedia of Biometrics (819— 825), USA: Springer.         [ Links ]

15. The Telegraph. (2011, 21 January). México to become first country to use iris scans on ID cards. Retrieved from www.telegraph.co.uk. http://www.telegraph.co.uk/news/worldnews/centralamericaandthecaribbean/mexico/8275086/Mexico-to-become-first-country-to-use-iris-scans-on-ID-cards.html        [ Links ]

16. Ganeshan, B., Theckedath, D., Young, R., & Chatwin, C. (2006). Biometric iris recognition system using a fast and robust iris localizaron and alignment procedure. Optics and Lasers in Engineering, 44(1), 1-24.         [ Links ]

17. Zhu, Y., Tan, T., & Wang, Y. (2000). Biometric Personal Identification Based on Iris Patterns. 15th International Conference on Pattern Recognition, Barcelona, Spain, 801-804.         [ Links ]

18. Vartiainen, J. (2009). Iris Recognition Systems and methods. Lappeenranta University of Technology, Lappeenranta, Finland.         [ Links ]

19. Iris ID Systems, Inc. (2012). lrisAccess7000, systems. Retrieved from http://www.irisid.com/irisaccess7000.         [ Links ]

20. MorphoTrust USA (s.f.). Iris Solutions. Retrieved from http://www.morphotrust.eom/pages/118-iris.         [ Links ]

21. Oki Electric Industry Co., Ltd. (2012). IRISPASS. Retrieved from http://www.oki.com/en/iris/        [ Links ]

22. Smart Sensors Ltd. (s.f.). Iris Station 2000. Retrieved from http://www.smartsensors.co.uk/information/iris-station%C2%AE-2000/        [ Links ]

23. AOptix Technologies, Inc. (2012). The Aoptix In Sight System. Retrieved; from http://www.aoptix.com/identity/insight-product-family        [ Links ]

24. Fully automated iris recognition system utilizing wide and narrow field of view. US patent 6,714,665 B1, 2004.         [ Links ]

25. Guo, G., Jones, M., Beardsley, P. (2005). A System for Automatic Iris Capturing. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download7doFiO.1.1.60.7271&rep=rep1&type=pdf        [ Links ]

26. Yoon, S., Jung, H.G., Suhr, J.K., & Kim, J. (2007). Non-intrusive Iris Image Capturing System Using Light Stripe Projection and Pan-Tilt-Zoom Camera. IEEE Conference on Computer Visión and Pattern Recognition (CVPR'07), Minneapolis, MN, USA, 1-7.         [ Links ]

27. Yoon, S., Jung, H.G., Park, K.R., & Kim, J. (2009). Nonintrusive Iris Image Acquisition System Based on a Pan-Tilt-Zoom Camera and Light Stripe Projection. Óptica! Engineering, 48(3), 037202-037202-15.         [ Links ]

28. Matey, J.R., Naroditsky, O., Hanna, K., Kolczynski, R., Lolacono, D.J., Mangru, S., Tinker, M., Zappia, T.M., & Zhao, W.Y. (2006). Iris on the Move: Acquisition of Images for Iris Recognition in Less Constrained Environments. Proceedings of the IEEE, 94(11), 1936-1947. (2006).         [ Links ]

29. SRI International. (2012). Iris on the Move Biometric Identification Systems. Retrieved from http://www.sri.com/engage/products-solutions/iris-move-biometric-identification-systems        [ Links ]

30. Fancourt, C, Bogoni, L., Hanna, K., Guo, Y., Wildes, R., Takahashi, N., & Jain, U. (2005). Iris recognition at a distance. Audio and Video-Based Biometric Person Authentication. Lecture Notes in Computer Science, 3546, 187-200.         [ Links ]

31. Matey, J., Ackerman, D., Bergen, J., & Tinker, M. (2008). Images for Iris Recognition in Less Constrained Environments, Advances in Biometrics, 1, 107-131,         [ Links ]

32. Daugman, J. (2007). New Methods in Iris Recognition. IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics, 37(5), 1167— 1175.         [ Links ]

33. Huang, Y.P., Luo, S.W., & Chen, E.Y. (2002). An efficient iris recognition system. International Conference on Machine Learning and Cybernetics, Beijing, China, 450-454.         [ Links ]

34. Park, K.R. & Kim, J. (2005). A real-time focusing algorithm for iris recognition camera. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 35(3), 441-444.         [ Links ]

35. Ma, L, Tan, T., Wang, Y., & Zhang, D. (2004). Efficient iris recognition by characterizing key local variations. IEEE Transactions on Image Processing, 13(6), 739-750.         [ Links ]

36. Krichen, E., Allano, L., Garcia-Salicetti, S., & Dorizzi, B. (2005). Specific texture analysis for iris recognition. Audio and Video Based Biometric Person Authentication, Lecture Notes in Computer Science, 3546, 23-30.         [ Links ]

37. Schmid, N.A., Ketkar, M.V., Singh, H., & Cukic, B. (2006). Performance analysis of iris-based identification system at the matching scores level. IEEE Transactions on Information Forensics and Security, 1(2), 154-168.         [ Links ]

38. Bowyer, K.W., Chang, K.I., Yan, P., Flynn, P.J., Hansley, E., & Sarkar, S. (2006). Multi-modal biometrics: an overview. Second Workshop on Multi-Modal User Authentication, Toulouse, France.         [ Links ]

39. Chang, K.I., Bowyer, K.W., & Flynn, P.J. (2005). An evaluation of multimodal 2D+3D faces biometrics. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(4), 619-624.         [ Links ]

40. Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., & Worek, W. (2006). Preliminary Face Recognition Grand Challenge results. 7th International Conference on Automatic Face and Gesture Recognition, Southampton, United Kingdom, 15-24.         [ Links ]

41. Goldstein, J., Angeletti R., Holzbach, M., Konrad, D., & Snijder, M. (2008). Large scale Biometrics Deployment in Europe: Identifying Challenges and Threats. JRC Scientific and Technical Reports        [ Links ]

42. Iris Image Interchange Format. ANSI INCITS 379-2004        [ Links ]

43. Information Technology - Biometric data interchange formats - Part 6: Iris Image Data. ISO/IEC 19794-6:2005        [ Links ]

44. JPEG, JBIG. (2007). The official site of the Joint Photographic Experts Group (JPEG) and Joint Bi-level Image experts Group (JBIG). Retrieved from http://www.jpeg.org/        [ Links ]

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons