Efficient and robust segmentation of less intrusively or non-cooperatively captured iris
images is still a challenging task in iris biometrics. This paper proposes a novel two-stage …

Traditional iris segmentation methods give good results when the iris images are taken
under ideal imaging conditions. However, the segmentation accuracy of an iris recognition …

Iris segmentation plays an important role in the iris recognition system, and the accurate
segmentation of iris can lay a good foundation for the follow-up work of iris recognition and …

Iris Biometrics: From Segmentation to Template Security provides critical analysis,
challenges and solutions on recent iris biometric research topics, including image …

Remote human identification using iris biometrics has high civilian and surveillance
applications and its success requires the development of robust segmentation algorithm to …

The recent widespread development of connected sensors, cloud, big data analytics, and
ubiquitous sensing technologies have facilitated cognitive Internet of things (CIoT) and its …

Iris recognition has drawn a lot of attention since the mid-twentieth century. Among all
biometric features, iris is known to possess a rich set of features. Different features have …

Automated iris segmentation is an important component of biometric identification. The role
of artificial intelligence, particularly machine learning and deep learning, has been …

Iris recognition typically involves three steps, namely, iris image preprocessing, feature
extraction, and feature matching. The first two steps of iris recognition have been well …

Noisy iris recognition under visible lighting has recently drawn much attention. This paper
proposes an effective method for visible light iris image matching by using multiple …