ANALYSIS OF IRIS RECOGNITION ON BASIS OF MATRIX MATCHING
Bhanu Gupta, Kanika Sharma, Randhir Singh · International journal of advance research and innovative ideas in education · 2018
Abstract: Iris recognition is a well-known biometric technique. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. In this work, we evaluate, modify and extend John Daugman’s method. However, published results have usually been produced under favorable conditions, and there have been no independent trials of the technology. The work presented here involves developing an ‘open- source iris recognition system in order to verify both the uniqueness of the human iris and also its performance as a biometric. Iris recognition systems capture an image from an individual's eye. The iris in the image is then segmented and normalized for feature extraction and matrix matching process. The iris recognition system consists of an automatic segmentation system, and is able to localize the circular iris and pupil region, excluding eyelids and eyelashes, and reflections. The extracted iris regions were normalized into a rectangular block with constant dimensions to account for imaging inconsistencies. This method can successfully detect all the pupil boundaries in the IIT Delhi Database and CASIA database and increase the recognition accuracy.