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Pair of Iris Recognition Using Feedforward Neural Networks


Affiliations
1 Department of Software Engineering, Periyar Maniammai University, Thanjavur, Tamil Nadu, India
2 Department of Computer Science Engineering, Periyar Maniammai University, Thanjavur, India
     

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Pair of iris recognition is very effective for person identification due to the iris unique features and the protection of the iris from the environment and aging. In addition it is well suitable to embark upon accidental or ophthalmological disease issue. This paper presents a simple methodology for pre-processing pair of iris images which means both left and right eye of human(instead of either right or left eye) and the design and training of feedforward artificial neural network for iris recognition system. Three different iris image data partitioning techniques and two data coding are proposed and explored. We also experiment with various number of hidden layers, number of neurons in each hidden layer, input format (binary vs. analog) percent of data used for training vs testing, and with the addition of noise. Our recognition system achieves high accuracy despite using simple data preprocessing and a simple neural network.


Keywords

Backpropagation Training Algorithm, Data Partitioning Feedforward Neural Networks, Pair of Iris Recognition, Pre-Processing.
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  • Pair of Iris Recognition Using Feedforward Neural Networks

Abstract Views: 140  |  PDF Views: 3

Authors

M. Chithra Devi
Department of Software Engineering, Periyar Maniammai University, Thanjavur, Tamil Nadu, India
T. Kavitha
Department of Computer Science Engineering, Periyar Maniammai University, Thanjavur, India

Abstract


Pair of iris recognition is very effective for person identification due to the iris unique features and the protection of the iris from the environment and aging. In addition it is well suitable to embark upon accidental or ophthalmological disease issue. This paper presents a simple methodology for pre-processing pair of iris images which means both left and right eye of human(instead of either right or left eye) and the design and training of feedforward artificial neural network for iris recognition system. Three different iris image data partitioning techniques and two data coding are proposed and explored. We also experiment with various number of hidden layers, number of neurons in each hidden layer, input format (binary vs. analog) percent of data used for training vs testing, and with the addition of noise. Our recognition system achieves high accuracy despite using simple data preprocessing and a simple neural network.


Keywords


Backpropagation Training Algorithm, Data Partitioning Feedforward Neural Networks, Pair of Iris Recognition, Pre-Processing.