Iris detection and recognition using 2 fold technique
Dinesh Kumar Vishwakarma, Divyansh Jain, Shantanu Rajora · 2017
The objective of this paper is to introduce a new integrated methodology for iris detection and recognition using a two fold method to deduce better results as compared to the existing techniques. The methodology primarily employs the Finite Impulse Response(FIR) and Gabor wavelet transform as for computing fundamentals. The figurative classification in the proposed algorithm is on the basis of euclidean distance. Thus the proposed algorithm solely works on construing the euclidean distances of the test sample with respect to that of the samples in the data set in the either fold procedures. Further the least euclidean distance measured is considered as the perfect match for the input test sample. As a result of extensive testing and implementation of the proposed algorithm/methodology in this paper, satisfactory accuracy and results are obtained as tested on Self Generated Dataset. The proposed algorithm focus on extensively using all the data available and retrievable from the human iris, specifically the red, green and blue segments, i.e RGB scheme unlike traditional iris based recognition wiz. computation on grayscale inputs, thus on the contrary, the methodology presented in this paper employs suitable color coding pattern using FIR(Finite Impulse Response) in addition to the Gabor filter texture classification technique.