Abstract:
Biometrics is a method for recognizing based
on physiological and behavioral characteristics. Iris
recognition is one of the robust biometric
technologies used for authentication applications. An
iris recognition system is composed of segmentation,
normalization, feature extraction and matching. The
performance of iris recognition system depends on
the selection of iris features. Most commercial iris
recognition systems used patented algorithms
developed by Daugman’s Gabor filter for feature
extraction. These methods have large computation.
To overcome this problem, a new effective method,
Secant Lines Segments Histogram, is proposed for
extracting features of iris. In this paper, Hough
Transform is applied for localizing the iris region.
The segmented iris is normalized using Daugman’s
Rubber Sheet Model. For extracting iris features,
Secant Lines Segments Histogram is used. The two
iris feature vectors are matched using Euclidean
Distance. The proposed iris recognition system
reduces the computation and time load for extracting
features of the iris.
