Advertisement

Multispectral Iris Acquisition System

  • David Zhang
  • Zhenhua Guo
  • Yazhuo Gong
Chapter

Abstract

Multispectral iris recognition is one of the most reliable biometrics in terms of recognition performance. This paper describes the design and implementation of a high-speed multispectral iris capture device, which consists of the following four parts: (1) capture unit; (2) illumination unit; (3) interaction unit; and (4) control unit. A multispectral iris image database is created by the proposed capture device, and then, we use the iris image-level fusion to further investigate the effectiveness of the proposed capture device by the 1-D Log-Gabor wavelet filter approach.

Keywords

Multispectral iris Acquisition system Fusion Recognition 

References

  1. Biom Technol (2005) Iris recognition in focus. Today 13(2): 9–11Google Scholar
  2. Burge MJ, Monaco MK (2009) Multispectral iris fusion for enhancement, interoperability, and cross wavelength matching. In: SPIE Defense, Security, and sensing, pp 73341D–73341DGoogle Scholar
  3. CASIA Iris Image Database (2005) http://www.cbsr.ia.ac.cn/IrisDatabase.htm
  4. Daugman JG (1993) High confidence visual recognition of persons by a test of statistical independence. IEEE Trans Pattern Anal Mach Intell 15(11):1148–1161CrossRefGoogle Scholar
  5. Daugman J (2004) How iris recognition works. IEEE Trans Circ Syst Video Technol 14(1):21–30CrossRefGoogle Scholar
  6. Daugman J (2007) New methods in iris recognition. IEEE Trans Syst Man Cybern B Cybern 37(5):1167–1175CrossRefGoogle Scholar
  7. Ebisawa Y (1998) Improved video-based eye-gaze detection method. IEEE Trans Instrum Meas 47(4):948–955CrossRefGoogle Scholar
  8. Gamassi M, Lazzaroni M, Misino M, Piuri V, Sana D, Scotti F (2005) Quality assessment of biometric systems: a comprehensive perspective based on accuracy and performance measurement. IEEE Trans Instrum Meas 54(4):1489–1496CrossRefGoogle Scholar
  9. He X, Yan J, Chen G, Shi P (2008) Contactless autofeedback iris capture design. IEEE Trans Instrum Meas 57(7):1369–1375CrossRefGoogle Scholar
  10. Hollingsworth KP, Bowyer KW, Flynn PJ (2009) The best bits in an iris code. IEEE Trans Pattern Anal Mach Intell 31(6):964–973CrossRefGoogle Scholar
  11. Iris Recognition from IRIS ID (2014) http://www.irisid.com/home
  12. Kang BJ, Park KR (2007) Real-time image restoration for iris recognition systems. IEEE Trans Syst Man Cybern B Cybern 37(6):1555–1566CrossRefGoogle Scholar
  13. Masek L (2003) Recognition of human iris patterns for biometric identification. Doctoral dissertation, Master’s thesis, University of Western AustraliaGoogle Scholar
  14. Mobile Dual Iris Capture Device (2014) http://www.crossmatch.com/i-scan-2/
  15. Ngo HT, Ives RW, Matey JR, Dormo J, Rhoads M, Choi D (2009) Design and implementation of a multispectral iris capture system. In: Signals systems and computers 2009 conference record of the forty-third Asilomar conference, pp 380–384Google Scholar
  16. Oki Introduces the IRISPASS®-WG Iris Recognition System with Automatic Iris Scanning Function (2002) http://www.oki.com/en/press/2002/z02011e.html
  17. Park KR, Kim J (2005) A real-time focusing algorithm for iris recognition camera. Syst Man Cybern Part C: IEEE Trans Appl Rev 35(3):441–444CrossRefGoogle Scholar
  18. Peretto L, Rovati L, Salvatori G, Tinarelli R, Emanuel AE (2007) A measurement system for the analysis of the response of the human eye to the light flicker. IEEE Trans Instrum Meas 56(4):1384–1390CrossRefGoogle Scholar
  19. Peters TH (2009) Effects of segmentation routine and acquisition environment on iris recognition. Doctoral dissertation, University of Notre DameGoogle Scholar
  20. Ross A, Pasula R, Hornak L (2006) Exploring multispectral iris recognition beyond 900 nm. In: Proceedings of the 2006 conference on computer vision and pattern recognition workshop: 51Google Scholar
  21. Shi P, Xing L, Gong Y (2003) A quality evaluation method of iris recognition system. Chin Pat 1(474): 345Google Scholar
  22. Tan T, Zhu Y, Wang Y (1999) Iris image capture device. Chin Pat 2(392):219Google Scholar
  23. Vilaseca M, Mercadal R, Pujol J, Arjona M, de Lasarte M, Huertas R, Imai FH (2008) Characterization of the human iris spectral reflectance with a multispectral imaging system. Appl Opt 47(30):5622–5630CrossRefGoogle Scholar
  24. Wildes RP (1997) Iris recognition: an emerging biometric technology. Proc IEEE 85(9):1348–1363CrossRefGoogle Scholar
  25. Wilkerson CL, Syed NA, Fisher MR, Robinson NL, Albert DM (1996) Melanocytes and iris color: light microscopic findings. Arch Ophthalmol 114(4):437–442CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Biometrics Research CentreThe Hong Kong Polytechnic UniversityHung HomHong Kong SAR
  2. 2.Shenzhen Key Laboratory of Broadband Network & Multimedia, Graduate School at ShenzhenTsinghua UniversityShenzhenChina
  3. 3.University of Shanghai for Science and TechnologyShanghaiChina

Personalised recommendations