Feature Matching in Iris Recognition System using MATLAB
Imran N, Narendra Kumar Rao B
Journal of Multimedia Processing and Technologies, Vol. 11, No. 2, 2020.
DOI: https://doi.org/10.6025/jmpt/2020/11/2/43-59
Link: http://www.dline.info/jmpt/fulltext/v11n2/jmptv11n2_1.pdf
Abstract:
Iris recognition system is a secure human authentication in biometric technology. Iris recognition system consists of five stages. They are Feature matching, Feature encoding, Iris  Normalization, Iris Segmentation and Image acquisition. In Image acquisition, the eye Image is captured from the CASIA database, the Image must have good quality with high resolution to process next steps. In Iris Segmentation, the Iris part is detected by using Hough transform technique and Canny Edge detection technique. Iris from an eye Image segmented. In normalization, the Iris region is converted from the circular region into a rectangular region by using polar transform technique. In feature encoding, the normalized Iris can be encoded
in the form of binary bit format by using Gabor filter techniques. In feature matching, the encoded Iris template is compared with database eye Image of Iris template and generated the matching score by using Hamming distance technique. Based on the matching score, we get the result. This project is developed using Image processing toolbox of Matlab software.