Biometric Iris Recognition System’s Software and Hardware Implementation Using Lab VIEW tool
MR Prasad1, Pavithra G2, TC Manjunath3*, Sandeep KV4 and Aditya TB5
1Associate Professor, Computer Science and Engineering, Vidya Vardhaka College of Engineering, Mysore, Karnataka, India
2Associate Professor, Electronics and Communication Engineering, Dayananda Sagar College of Engineering, Bangalore, Karnataka, India
3Professor and Head of the Department, Electronics and Communication Engineering, Dayananda Sagar College of Engineering, Bangalore, India
4Assistant Professor, Electronics and Communication Engineering, Jain Institute of Technology, Davanagere, Karnataka, India
5Second Year BE UG Student, Department of Computer Science and Engineering, PES University, Bangalore, India
*Corresponding Author: TC Manjunath, Professor and Head of the Department, Electronics and Communication Engineering, Dayananda Sagar College of
Engineering, Bangalore, India.
October 16, 2022; Published: December 23, 2022
In this paper, the software implementation of the automatic biometric iris recognition system using the proposed methodologies under unconstrained environments is being presented with the proposed block-diagrams developed in the LabVIEW environment. 3 different contributions are presented here in this paper, which is a part of the research work undertaken by the research scholar. It also describes the various steps that are used in the proposed methodologies and all the basic blocks involved in the design process of each contribution. In order to achieve the better accuracy, performance and error rate than the existing methods done by earlier researchers, 3 different iris recognition system techniques under unconstrained environments have been proposed which involves different feature extraction techniques and matching or classification algorithms and some of them being compared with the earlier works done by other researchers, thus establishing the supremacy of the work done by us. Matlab tool is used for the software implementation purposes due to its add-on features and support provided. Codes are developed in the LabVIEW environment as .vi files. The developed .vi files are run; the simulation results are observed and the discussion on the simulation results are presented for each contribution. Finally, the overall conclusions are drawn on the observation of all the 3-contributory works. Hardware implementation using a Micro-controller is also proposed in this paper, which has yielded very good results. A number of algorithms for iris recognition has been designed in the proposed research work which is being presented in a abstracted manner in this research paper.
Keywords: Biometrics; Iris; Authentication; Recognition; Identification; Classifiers; Simulation; Matlab; LabVIEW; Neural Network; Database; Image; Pre-processing; Segmentation; Algorithm; Histogram; Filter; Edge Detection; Normalization; Wavelets; Coding; GUI; Unconstraints; Constraints; Hardware; Software; Implementation
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