RECOGNITION OF HUMAN IRIS PATTERNS FOR BIOMETRIC IDENTIFICATION
JOURNAL OF ENGINEERING AND APPLIED SCIENCE • 2007
Publication Information
Authors
Eman Monir, Ahmed Farag Seddik, Ebada Sarhan
Keywords
Biometric, iris recognition, pupil, iris, image segmentation.
Journal
JOURNAL OF ENGINEERING AND APPLIED SCIENCE
Publisher
JEAS
Volume
54
Issue
6
Pages
635-651
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
In this paper, efficient biometric security technique for iris recognition system
with high performance and high confidence is proposed. The proposed system is based
on an empirical analysis of the iris image and it is split into several steps using local
image properties. The system steps are, the preprocessing stage; determine the location
of the iris boundaries; converting the iris boundary to the stretched polar coordinate
system; extracting the iris code based on texture analysis using wavelet transforms;
and classification of the iris code. The proposed system uses the haar wavelet
transforms for texture analysis, and it depends heavily on knowledge of the general
structure of a human iris. Experimental results showed that the proposed technique has
a quite effective performance and encouraging results, with error rate 0.6% in case of
CASIA database and 16.6% in Ubiris database. The proposed technique could
potentially improve iris identification efficiency, the system only needs to store 25 x
25 images feature vector which increases the matching process speed and decreases
the system complexity compared with other techniques. The subject image is not
compared to every image in the database,
with high performance and high confidence is proposed. The proposed system is based
on an empirical analysis of the iris image and it is split into several steps using local
image properties. The system steps are, the preprocessing stage; determine the location
of the iris boundaries; converting the iris boundary to the stretched polar coordinate
system; extracting the iris code based on texture analysis using wavelet transforms;
and classification of the iris code. The proposed system uses the haar wavelet
transforms for texture analysis, and it depends heavily on knowledge of the general
structure of a human iris. Experimental results showed that the proposed technique has
a quite effective performance and encouraging results, with error rate 0.6% in case of
CASIA database and 16.6% in Ubiris database. The proposed technique could
potentially improve iris identification efficiency, the system only needs to store 25 x
25 images feature vector which increases the matching process speed and decreases
the system complexity compared with other techniques. The subject image is not
compared to every image in the database,
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