A Score Level Fusion Scheme for Iris Recognition

The main aim of this paper is to analyse the iris texture which becomes the basis of feature extraction. In Iris Recognition System (IRS), feature extraction is one of the significant steps which is followed by a matching process. The proposed method takes into account three techniques: DSIFT, HOG and DCT. These techniques are individually employed on the blocks that correspond to the regions of interest, not occluded by noise. A block-wise matching of obtained feature vectors is carried out using a standard measure. The true match of the system relies on the three aforementioned techniques which make the system more robust. The experimental results are reported on CASIA-IrisV1 database. The obtained outcomes indicate that the performance of the system increased significantly due to the score level fusion of the matching that makes it suitable for the iris recognition related applications.