Analysis & Performance Evolution of IRIS Recognition SVD and EBP Algorithms using Neural Network Classifier

Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus it is the most promising for high security environments. Hence numbers of IRIS recognition algorithms are available, techniques we purposed such as SVD (singular value decomposition) this technique will be used to extract the features of iris.The nonuseful information such as sclera, pupil, eyelashes and eyelids are removed and Region of Interest (ROI) is extracted. Then the Iris template is generated to reduce the information thereby concentrating only on the ROI. The details of this combined system named as Iris Pattern recognition using neural Network Approach. All IRIS recognition algorithms are evaluated on the basis of classification rate obtained after changing different parameters such as number of classes, Training and Testing patterns, SVDTo reduce complexity of layered neural network the dimension of input vectors are optimized using Singular Value Decomposition (SVD). The optimum classification values are obtained with SVD 20 dimension and maximum number of classes as 9 with the state-of-the art computational resources. The details of this combined system named as SVD-EBD system for Iris pattern recognition.