Open AccessLocal Binary Pattern Based Iris Recognition Model
Publication year - 2020
Publication title -
international journal for research in engineering application and management
Language(s) - English
Resource type - Journals
ISSN - 2454-9150
DOI - 10.35291/2454-9150.2020.0004
Subject(s) - local binary patterns , iris recognition , hamming distance , histogram , pattern recognition (psychology) , artificial intelligence , biometrics , computer science , binary number , classifier (uml) , iris (biosensor) , k nearest neighbors algorithm , computer vision , mathematics , image (mathematics) , algorithm , arithmetic
Iris is a unique biometric tool, secure and reliable in recognizing an individual based on the texture information of human physiology. The Local Binary Pattern method uses descriptors based on histograms of Local Binary Pattern. In developed algorithm, Local Binary Pattern (LBP) histograms of iris images are extracted and concatenated into single enhanced histogram. It can be computed by nearest neighbor classifier and iris recognition is performed using Hamming distance as dissimilarity measure. We have conducted experimentation on CASIA dataset. From the experimental results, it is proved that the Robust LBP technique for iris recognition is more accurate than the conventional LBP.