For iris recognition in non-cooperative environments, iris segmentation has been regarded
as the first most important challenge still open to the biometric community, affecting all …

State-of-the-art iris segmentation algorithms exhibit poor performance for non-ideal data,
which is mainly because of the noise such as low contrast, non-uniform illumination …

In the daily application of an iris-recognition-at-a-distance (IAAD) system, many ocular
images of low quality are acquired. As the iris part of these images is often not qualified for …

Undersampling in the detector array degrades the performance of iris-recognition imaging
systems. We find that an undersampling of 8× 8 reduces the iris-recognition performance by …

Cross-spectral iris recognition represents the ability of the system to identify the iris images
acquired in different electromagnetic spectrums. An iris captured in the near-infrared …

Most of the classical iris recognition systems require cooperation from users and assume
ideal conditions during iris image acquisition. In uncooperative and unconstrained …

In traditional iris recognition systems, majority of researches improves the recognition
performance for frontal images by ignoring the challenging issues including corneal …

One of the most common and successful biometric frameworks is iris recognition, which has
yielded promising results in systems of access control and identity authentication. Recent …

Iris segmentation is an essential module in iris recognition because it defines the effective
image region used for subsequent processing such as feature extraction. Traditional iris …

Ocular biometrics in the visible spectrum has emerged as an area of significant research
activity. In this paper, we propose a hybrid convolution-based model, for verifying a pair of …