Iris localization based on integro-differential operator for unconstrained infrared iris images

Abstract

Iris localization is an important step for high accuracy iris recognition systems and it becomes difficult for iris images captured in unconstrained environments. The proposed method localizes irises in unconstrained infrared iris images having non-ideal issues such as severe reflections, eyeglasses, low contrast, low illumination and occlusions by eyebrow hair, eyelids and eyelashes. In the proposed method, the iris image is first preprocessed using morphological operation to remove reflections and make it suitable for subsequent steps. The proposed method detects pupil using Daugman's integro-differential operator (IDO) and iris's outer boundary is detected using proposed modified Daugman's IDO. The proposed method proposes a technique based on thresholding and morphological operation to reduce the number of pixels on which the IDO is applied for detecting pupil which improves the time performance and accuracy as well. The method was tested with CASIA-Iris-Thousand, version 4.0 (CITHV4) iris database which contains challenging images having non-ideal issues as described before. The average accuracy of the proposed method is 99.3% and average time cost per image is 1.86 seconds for CITHV4. The proposed method shows improvement in both accuracy and time when compared with some published state-of-the-art iris localization methods in the literature.