Subscription or Fee Access
A Novel Iris Recognition System Based on Central Force Optimization
Iris Recognition has emerged as a reliable biometric technique in the recent past. Huge amount of work has been carried out continuously to improve its performance and accuracy. This paper proposes an iris recognition system using FFBNN-CFO. CFO is a novel metaheuristic technique which works on the basis of physical kinematics, and can be used for optimization of Neural Network parameters. Initially the eye images are preprocessed using adaptive median filter to remove salt and pepper noise. Then, the statistical features are extracted from the iris and pupil region. These features are then used to train the FFBNN. During training, FFBNN parameters are optimized by CFO to improve the accuracy of the system. In the testing phase the performance of the proposed iris recognition system is tested with the help of sufficient number of eye images from 2 major databases MMU1 and UBIRIS. The performance of the proposed method is compared and contrasted with other methods such as Adaptive Acceleration Particle Swarm Optimization (AAPSO), Particle Swarm Optimization (PSO) and FFBNN. The comparison shows that, the proposed iris recognition system based on FFBNN-CFO, gives higher recognition accuracy as compared to FFBNN-AAPSO, FFBNN-PSO and FFBNN.
Feed Forward Back propagation Neural Network (FFBNN), Adaptive Median Filter, Feature Extraction, Iris Recognition, Central Force Optimization (CFO).
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.