%0 Journal Article %1 noauthororeditor %A Sarode, Nivedita S. %A Patil, A. M. %D 2014 %E Kumar, Dr. Shiv %J International Journal of Innovative Science and Modern Engineering (IJISME) %K %N 10 %P 34-40 %T Review of Iris Recognition: An evolving Biometrics Identification Technology %U https://www.ijisme.org/wp-content/uploads/papers/v2i10/J07150921014.pdf %V 2 %X A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Unlike other biometric such as fingerprints and face recognition, the distinct aspect of iris comes from randomly distributed features. Iris recognition is regarded as the most reliable and accurate biometric identification system available. This paper provides the review of related work in the iris recognition. A general framework of the iris recognition system is proposed and finally the advantages and disadvantages of the iris recognition technology are analyzed. It is commonly accepted that users of a biometric system may have differing degrees of accuracy within the system. Some people may have trouble authenticating, while others may be particularly vulnerable to impersonation. The estimation results reveal, as expected, that a wide variety of factors affect security transit times including the number of enplaning seats (reflecting flight schedules), weather conditions, day of week, as well as obvious variables such as traveler volume and the number of open security lanes. The recognition accuracy of a single biometric authentication system is often much reduced due to the environment, user mode and physiological defect. Iris and Retina biometric recognition offers a highly reliable solution to person authentication. Instead of using the entire iris code, only the bits that are consistent in the iris code called the best bits are considered in the feature matching process. This reduces the computational time and storage requirements of iris code. To enhance the performance of recognition, the iris recognition process is applied to left and right irises separately and the corresponding distance scores are generated for each iris of a person. These scores are combined using the weighted sum fusion rule which further increases the recognition rate. Iris recognition system is composed of segmentation, normalization, feature encoding and matching.

@article{noauthororeditor, abstract = {A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Unlike other biometric such as fingerprints and face recognition, the distinct aspect of iris comes from randomly distributed features. Iris recognition is regarded as the most reliable and accurate biometric identification system available. This paper provides the review of related work in the iris recognition. A general framework of the iris recognition system is proposed and finally the advantages and disadvantages of the iris recognition technology are analyzed. It is commonly accepted that users of a biometric system may have differing degrees of accuracy within the system. Some people may have trouble authenticating, while others may be particularly vulnerable to impersonation. The estimation results reveal, as expected, that a wide variety of factors affect security transit times including the number of enplaning seats (reflecting flight schedules), weather conditions, day of week, as well as obvious variables such as traveler volume and the number of open security lanes. The recognition accuracy of a single biometric authentication system is often much reduced due to the environment, user mode and physiological defect. Iris and Retina biometric recognition offers a highly reliable solution to person authentication. Instead of using the entire iris code, only the bits that are consistent in the iris code called the best bits are considered in the feature matching process. This reduces the computational time and storage requirements of iris code. To enhance the performance of recognition, the iris recognition process is applied to left and right irises separately and the corresponding distance scores are generated for each iris of a person. These scores are combined using the weighted sum fusion rule which further increases the recognition rate. Iris recognition system is composed of segmentation, normalization, feature encoding and matching.}, added-at = {2021-09-21T13:47:03.000+0200}, author = {Sarode, Nivedita S. and Patil, A. M.}, biburl = {https://www.bibsonomy.org/bibtex/2e2f354bcb1589df89cf69e3d054d2209/ijisme_beiesp}, editor = {Kumar, Dr. Shiv}, interhash = {60d32ac2901b49b37d29c898de201357}, intrahash = {e2f354bcb1589df89cf69e3d054d2209}, issn = {2319-6386}, journal = {International Journal of Innovative Science and Modern Engineering (IJISME)}, keywords = {}, language = {En}, month = {September}, number = 10, pages = {34-40}, timestamp = {2021-09-21T13:47:03.000+0200}, title = {Review of Iris Recognition: An evolving Biometrics Identification Technology}, url = {https://www.ijisme.org/wp-content/uploads/papers/v2i10/J07150921014.pdf}, volume = 2, year = 2014 }