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.

Babasaheb G Patil and Dr. Mrs. Shaila Subbaraman, “SVD-EBP Algorithm for Iris Pattern Recognition” International Journal of Advanced Computer Science and Applications(IJACSA), 2(12), 2011. http://dx.doi.org/10.14569/IJACSA.2011.021217

@article{Patil2011,
title = {SVD-EBP Algorithm for Iris Pattern Recognition},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2011.021217},
url = {http://dx.doi.org/10.14569/IJACSA.2011.021217},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {12},
author = {Babasaheb G Patil and Dr. Mrs. Shaila Subbaraman},
}