Abstract: In this paper we describe Iris recognition using Modified Fuzzy Hypersphere Neural Network (MFHSNN) with its learning algorithm, which is an extension of Fuzzy Hypersphere Neural Network (FHSNN) proposed by Kulkarni et al. We have evaluated performance of MFHSNN classifier using different distance measures. It is observed that Bhattacharyya distance is superior in terms of training and recall time as compared to Euclidean and Manhattan distance measures. The feasibility of the MFHSNN has been successfully appraised on CASIA database with 756 images and found superior in terms of generalization and training time with equivalent recall time.

S Chowhan, U. V. Kulkarni and G. N. Shinde, “Iris Recognition Using Modified Fuzzy Hypersphere Neural Network with different Distance Measures” International Journal of Advanced Computer Science and Applications(IJACSA), 2(6), 2011. http://dx.doi.org/10.14569/IJACSA.2011.020619

@article{Chowhan2011,
title = {Iris Recognition Using Modified Fuzzy Hypersphere Neural Network with different Distance Measures},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.020619},
url = {http://dx.doi.org/10.14569/IJACSA.2011.020619},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {6},
author = {S Chowhan and U. V. Kulkarni and G. N. Shinde}
}