NDLI: Robust human iris pattern recognition system using neural network approach

Content Provider	IEEE Xplore Digital Library
Author	Khedkar, M.M. Ladhake, S.A.
Copyright Year	2013
Description	Author affiliation: Sipna Coll. of Eng. & Techi, Amravati, India (Khedkar, M.M.; Ladhake, S.A.)
Abstract	This paper proposes a prototype model of robust iris pattern recognition (PR) system for classification of ten different persons using neural network. Feature extraction algorithms are developed and an optimal feature vector comprising of features in relation to image statistics, texture and 2-D transform domain is formed. It is observed that 2D Walsh Hadamard Transform (WHT) entails the best performance as compared to other image transforms. Different neural network configurations, such as, Multi Layer Perceptron (MLP), Radial Basis Function (RBF) and Support Vector Machine (SVM) are implemented after systematically varying the concerned parameters of the respective networks and MLP with single hidden layer is seen to outperform all others with respect to performance on cross validation dataset derived from CASIA iris image database. Further, the sensitivity analysis is carried out over this network in order to reduce time and space complexity of the network. To make this network more robust; controlled Gaussian and Uniform noise are injected in all input features and it is noticed that for both types of noise, the proposed PR system can sustain the variance up to 0.1.
Sponsorship	IEEE Madras Sect.
Starting Page	78
Ending Page	83
File Size	380019
Page Count	6
File Format	PDF
ISBN	9781467357869
e-ISBN	9781467357883
DOI	10.1109/ICICES.2013.6508356
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-02-21
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensitivity analysis Noise Vectors Multi layer Perceptron Support vector machine Gaussian Noise Training Support vector machines Pattern recognition system Uniform Noise Neural networks Radial Basis Function Walsh Hadamard Transform Feature extraction Iris recognition
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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