Research Article
Iris Recognition based Biometric identification using Neural Networks
@INPROCEEDINGS{10.4108/eai.27-2-2020.2303175, author={Reend Tawfik Mohammed and Shafqat Ul Ahsaan and Harleen Kaur}, title={Iris Recognition based Biometric identification using Neural Networks}, proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2021}, month={3}, keywords={biometrics iris recognition normalization localization neural networks iris encoding neural network back propagation neural network}, doi={10.4108/eai.27-2-2020.2303175} }- Reend Tawfik Mohammed
Shafqat Ul Ahsaan
Harleen Kaur
Year: 2021
Iris Recognition based Biometric identification using Neural Networks
ICIDSSD
EAI
DOI: 10.4108/eai.27-2-2020.2303175
Abstract
Iris identification is one of the striking biometric identification procedure for recognizing human beings based on physical behaviour. The texture of iris is unique and its’ anatomy varies from individual to individual. The Iris recognition system works in three stages: in first phase the iris is localized and stored in the database. In this paper, we have elaborated multiple methods for the detection of iris based on neural networks. The Iris is extracted from an image database and in second pass normalization is performed and next is the enhancement. There are many biometric techniques available for distinguishing between the physical or behavioral characteristics of human beings. The physical features of human beings are unique, and they never change this has conducted to a significant development in the field of iris recognition. Iris detection is considered to be a very reliable field because of its texture’s random variation. This paper highlighted the use of Neural Networks for the recognition of iris. We focus on the current research works that have been carried in the field of bioinformatics used for the identity of an individual. It includes many methods like localization, normalization, comparison, and encoding. This recognition field has many practical and research applications. The region of the Iris is localized in the dataset for Iris image is generated, and later pattern recognition is carried out.
