Iris recognition based on statistical assessment of wavelet coefficients
by Xing Ming, Zhi-Hui Li, Yuan-Ning Liu, Zheng-Xuan Wang
International Journal of Computer Applications in Technology (IJCAT), Vol. 26, No. 3, 2006

Abstract: This paper presents a new iris recognition method based on the statistical assessment of wavelet coefficients. For the matrix of wavelet coefficients generated by the one-dimensional wavelet multi-scale decomposition, the method presented uses statistical assessment to determine the significant wavelet coefficients at different scales and then transforms them into a binary vector to represent the iris features. The Hamming distance classifier is adopted to perform pattern matching between an input iris image and an enrolment template. The final experiments show promising results for iris recognition.

Online publication date: Mon, 07-Aug-2006

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com