TITLE:
Identity Verification of Individuals Based on Retinal Features Using Gabor Filters and SVM
AUTHORS:
Mohamed A. El-Sayed, M. Hassaballah, Mohammed A. Abdel-Latif
KEYWORDS:
Image Preprocessing, Gabor Filter, SVM, Authentication, Identification, Verification, Retinal Features, Feature Extraction, Query Image
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.7 No.1,
February
29,
2016
ABSTRACT: Authentication reliability of individuals
is a demanding service and growing in many areas, not only in the military
barracks or police services but also in applications of community and civilian,
such as financial transactions. In this paper, we propose a human verification
method depends on extraction a set of retinal features points. Each set of
feature points is representing landmarks in the tree of retinal vessel.
Extraction and matching of the pattern based on Gabor filters and SVM are
described. The validity of the proposed method is verified with experimental
results obtained on three different commonly available databases, namely STARE,
DRIVE and VARIA. We note that the proposed retinal verification method gives
92.6%, 100% and 98.2% recognition rates for the previous databases,
respectively. Furthermore, for the authentication task, the proposed method
gives a moderate accuracy of retinal vessel images from these databases.