Abstract

Iris recognition is a biometric system for access control that uses the most unique characteristic of the human body, the iris employed in automated border crossings, national ID systems, etc. This paper illustrates techniques to improve performance of iris recognition system based on stationary images using NI LabVIEW (Vision Module). Region of interest segmentation and localization of iris using canny edge detection is performed. And normalization of iris is performed using the Gabor filter. Local Binary Pattern (LBP) is used for feature vectors extraction and Learning Vector Quantization (LVQ) performs classification. Here, matching is performed using the hamming distance. Also we create a LabVIEW database for storing the information of the users. All the images used in this paper were collected from the Chinese Academy Of Sciences Institute of Automation (CASIA) iris database VI. 0 with 108 subjects in it.

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