http://iet.metastore.ingenta.com
1887

Infrared imaging of hand vein patterns for biometric purposes

Infrared imaging of hand vein patterns for biometric purposes

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Computer Vision — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A novel non-invasive imaging technique to image the vein patterns in various parts of the hand for biometric purposes is evaluated. Two imaging methods are investigated: far-infrared (FIR) thermography and near-infrared (NIR) imaging. Experiments involving data acquisition from various parts of the hand, including the back of the hand, palm and wrist, were carried out using both imaging techniques. Analysis of the data collected shows that FIR thermography is less successful at capturing veins in the palm and wrist. FIR thermography can capture the large veins in the back of the hand, but it is sensitive to ambient temperature and humidity conditions as well as human body temperature. NIR imaging produces good quality images when capturing veins in the back of the hand, palm and wrist. NIR imaging is also more tolerant to changes in the environment and body condition but faces the problem of pattern corruption because of visible skin features being mistaken for veins. This corruption is not present in FIR imaging. An initial biometric system is investigated to test both FIR and NIR images for biometric purposes. The results show all the subjects were correctly identified, which indicates vein pattern biometrics with infrared imaging is a potentially useful biometric.

References

    1. 1)
      • Ratha, N.K., Senior, A., Bolle, R.M.: `Tutorial on automated biometrics', Proc. Int. Conf. Advances in Pattern Recognition, March 2001, Rio de Janeiro, Brazil.
    2. 2)
      • Wang, L., Leedham, C.G.: `A thermal hand vein pattern verification system', Proc. Int. Conf. Advances in Pattern Recognition, August 2005, Bath, UK.
    3. 3)
      • Cross, J.M., Smith, C.L.: `Thermographic imaging of subcutaneous vascular network of the back of the hand for biometric identification', Proc. IEEE 29th Int. Carnahan Conf. Security Technology, October 1995, Sanderstead, Surrey, UK.
    4. 4)
      • Im, S.-K., Park, H.-M., Kim, S.-W., Chung, C.-K., Choi, H.-S.: `Improved vein pattern extracting algorithm and its implementation', Digest of Technical Papers of Int. Conf. Consumer Electronics, June 2000.
    5. 5)
    6. 6)
    7. 7)
      • Fujitsu Laboratories Ltd: ‘Fujitsu Laboratories develops technology for world's first contactless palm vein pattern biometric authentication system’. [Online March 2003], available at: http://pr.fujitsu.com/en/news/2003/03/31.html.
    8. 8)
      • A.K. Jain , R.M. Bolle , S. Pankanti . (2001) Biometrics: personal identification in networked society.
    9. 9)
      • P. MacGregor , R. Welford . Veincheck: imaging for security and personnel identification. Adv. Imaging , 7 , 52 - 56
    10. 10)
      • Hawkes, P.L., Clayden, D.O.: `Veincheck research for automatic identification of people', Presented at the Hand and Fingerprint Seminar at NPL, September 1993.
    11. 11)
      • D.C. Harris . (1992) Infrared window and dome materials.
    12. 12)
      • S. Fantini , M.A. Franceschini , V.V. Tuchin . (2002) Frequency-domain techniques for tissue spectroscopy and imaging, Handbook of optical biomedical diagnostics.
    13. 13)
      • L. Hong , Y. Wan , A. Jain . Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. Pattern Anal. Mach. Intell. , 8 , 777 - 789
    14. 14)
      • C.Y. Suen , T.Y. Zhang . A fast parallel algorithm for thinning digital patterns. Commun. ACM , 3 , 236 - 239
    15. 15)
      • W.J. Ruchlidge . Efficiently locating objects using Hausdorff distance. Int. J. Comput. Vis. , 251 - 270
    16. 16)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi_20070009
Loading

Related content

content/journals/10.1049/iet-cvi_20070009
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address