Iris Recognition Using Image Moments and k-Means Algorithm

Joint Authors

Khan, Sher Afzal
Islam, Saeed
Ahmad, Farooq
Khan, Yaser Daanial

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-04-01

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

This paper presents a biometric technique for identification of a person using the iris image.

The iris is first segmented from the acquired image of an eye using an edge detection algorithm.

The disk shaped area of the iris is transformed into a rectangular form.

Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments.

Images are clustered using the k-means algorithm and centroids for each cluster are computed.

An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed.

The described model exhibits an accuracy of 98.5%.

American Psychological Association (APA)

Khan, Yaser Daanial& Khan, Sher Afzal& Ahmad, Farooq& Islam, Saeed. 2014. Iris Recognition Using Image Moments and k-Means Algorithm. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1050773

Modern Language Association (MLA)

Khan, Yaser Daanial…[et al.]. Iris Recognition Using Image Moments and k-Means Algorithm. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1050773

American Medical Association (AMA)

Khan, Yaser Daanial& Khan, Sher Afzal& Ahmad, Farooq& Islam, Saeed. Iris Recognition Using Image Moments and k-Means Algorithm. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1050773

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1050773