Performance Analysis and Recognition of Iris Patterns for Human Authentication Using a Modified Approach
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Abstract
With the increasing demand for profound security in our daily lives, reliable
newlinepersonal identification through biometrics is currently an active topic in the literature of
newlinepattern recognition. Iris recognition is one of important biometric recognition approach in a
newlinehuman identification that is becoming very active topic in research and practical
newlineapplication. Once the image of the iris has been captured using a standard camera, the
newlineauthentication process, involving the comparison of current subject s iris with the stored
newlineversion, is one of the most accurate with very low false acceptance and rejection rates.
newlineThe main aim of the thesis is to study about iris recognition system which includes iris
newlinelocalization and normalization by using rubber sheet model, feature extraction using Gabor
newlineWavelet as well as template matching by Hamming distance. Compression technique is used
newlineto compress the eye image and this compressed eye is used for the localization of the inner
newlineand outer boundaries of the iris region. We investigated that the effect of compression on iris
newlinerecognition system accurately identifies individual s using different distance measures.
newlineIn this thesis work, we proved that it is possible to improve the reliability of the
newlinesystem by choosing a portion of the iris instead of whole extension of the iris. Initially,
newlineportion of the iris pattern is extracted using Gabor Wavelet(GW) and later, different
newlinetechniques such as Histogram of Oriented Gradient (HOG) and Local Binary Pattern
newline(LBP) are used for feature extraction to identify a person in successful manner with low
newlinefalse acceptance rate and with low false rejection rate.
newlineFinally, the iris features extracted using GW, HOG and LBP are taken as input and
newlinefed to Back Propagation Neural Network for classification. We implemented prominent
newlineiris recognition algorithm in MATLAB.
newlineThe system is to be composed of a number of sub-systems which correspond to each stage of iris recognition.