Iris recognition is a reliable and accurate biometric identification system for user authentication. It is used for capturing an image of an individual’s eye. The performance of iris recognition systems is measured using segmentation. Segmentation is used to localize the correct iris region in the particular portion of an eye and it should be done accurately and correctly for removing the eyelids, eyelashes, reflection, and pupil noises present in the iris region. In our paper, we are using Daughman’s Algorithm segmentation method for Iris Recognition. The segmented iris region was normalized to minimize the dimensional inconsistencies between iris regions. The features of the iris were encoded using a convolution theorem. The Hamming distance was included as a matching metric, which gave the measure of how many bits disagreed between the templates of the iris.
Published In IJRAR ( www.ijrar.org ) UGC Approved ( Journal No : 43602 ) & 5.75 Impact Factor | Volume 6 Issue 2 | May,2019 | Paper ID : IJRAR19K2025 | Registration ID : 203947
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