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

Hand vein biometry based on geometry and appearance methods

Hand vein biometry based on geometry and appearance methods

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

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(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 Title Publication 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.

Many biometric systems, such as face, fingerprint and iris have been studied extensively for personal verification and identification purposes. Biometric identification with vein patterns is a more recent approach that uses the vast network of blood vessels underneath a person's skin. These patterns in the hands are assumed to be unique to each individual and they do not change over time except in size. As veins are under the skin and have a wealth of differentiating features, an attempt to copy an identity is extremely difficult. These properties of uniqueness, stability and strong immunity to forgery of the vein patterns make it a potentially good biometric trait which offers greater security and reliable features for personal identification. In this study, the authors present a novel hand vein database and a biometric technique based on the statistical processing of the hand vein patterns. The BOSPHORUS hand vein database has been collected under realistic conditions in that subjects had to undergo the procedures of holding a bag, pressing an elastic ball and cooling with ice, all exercises that force changes in the vein patterns. The applied recognition techniques are a combination of geometric and appearance-based techniques and good identification performances have been obtained on the database.

References

    1. 1)
      • S.Z. Li , A.K. Jain . (2009) Encyclopedia of biometrics.
    2. 2)
    3. 3)
      • A.K. Jain , P. Flynn , A.A. Ross . (2008) Handbook of biometrics.
    4. 4)
    5. 5)
    6. 6)
      • Zhou, Y.K., Kumar, A.: `Contactless palmvein identification using multiple representations', Proc. BTAS 10, 2010, Washington, DC.
    7. 7)
      • Wang, Z., Zhang, B., Chen, W., Gao, Y.: `A performance evaluation of shape and texture based methods for vein recognition', Congress on Image and Signal Processing, Sanya, China, 27–30 May 2008, p. 659–661, vol. 2.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
      • Ding, Y., Zhuang, D., Wang, K.: `A study of hand vein recognition method', Proc. IEEE Int. Conf. on Mechatronics and Automation, 2005.
    13. 13)
      • Watec: Specifications of the WAT-902H2 ULTIMATE Camera, June 2010, http://www.watec.co.jp/english/bw/wat_902_ultimate.html.
    14. 14)
    15. 15)
    16. 16)
    17. 17)
    18. 18)
    19. 19)
      • D.D. Lee , H.S. Seung . Algorithms for non-negative matrix factorization. Adv. Neural Inf. Process. Syst. , 556 - 562
    20. 20)
      • P.O. Hoyer . Non-negative matrix factorization with sparseness constraints. J. Mach. Learn. Res. , 1457 - 1469
    21. 21)
    22. 22)
    23. 23)
      • Gokberk, B., Salah, A.A., Akarun, L.: `Rank-based decision fusion for 3D shape-based face recognition', Audio- and Video-Based Biometric Person Authentication (AVBPA), July 2005.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cvi.2010.0175
Loading

Related content

content/journals/10.1049/iet-cvi.2010.0175
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address