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SVD-EBP Algorithm for Iris Pattern Recognition
BibTeX
@MISC{Babasaheb_svd-ebpalgorithm,
author = {Mr. Babasaheb and G. Patil and Dr. Mrs and Shaila Subbaraman},
title = {SVD-EBP Algorithm for Iris Pattern Recognition},
year = {}
}
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Abstract
Abstract — This paper proposes a neural network approach based on Error Back Propagation (EBP) for classification of different eye images. To reduce the complexity of layered neural network the dimensions of input vectors are optimized using Singular Value Decomposition (SVD). The main objective of this work is to prove usefulness of SVD to form a compact set of features for classification by EBP algorithm. The results of our work indicate that optimum classification values are obtained with SVD dimensions of 20 and maximum number of classes as 9 with the state-of-the art computational resources The details of this combined system named as SVD-EBP system for Iris pattern recognition and the results thereof are presented in this paper. Keywords- Singular value decomposition (SVD); Error back Propagation (EBP). I.
Keyphrases
iris pattern recognition svd-ebp algorithm svd dimension singular value decomposition input vector neural network approach keywords singular value decomposition ebp algorithm error back propagation svd-ebp system maximum number layered neural network optimum classification value different eye image combined system compact set main objective state-of-the art computational resource
