Iris Features Extraction and Recognition based on the Local Binary Pattern Technique
Mohammed A. Taha, Hanaa Mohsin Ahmed · 2021
The current iris identification system offers accurate and reliable results based on near-infrared light (NIR) images when images are taken in a restricted area with the fixed-distance user cooperation. However, for the colour eye images obtained under visible wavelength (VW) without collaboration among the users, the efficiency of iris recognition degrades because of noise such as eye blurring images, eye lashing, occlusion, and reflection. This work aims to use the Local Binary Pattern (LBP) to retrieve the iris’s characteristics in both NIR iris images and visible spectrum. This approach is used and evaluated on the CASIA v1and ITTD v1 databases as NIR iris image and UBIRIS v1 as a colour image. The results showed a high accuracy rate (99.2 %) on CASIA v1, (99.4) on ITTD v1, and (86%) on UBIRIS v1 evaluated by comparing to the other methods.