Most state-of-the-art iris recognition algorithms claim to perform with a very high recognition
accuracy in a strictly controlled environment. However, their recognition accuracies …

One of the main challenges faced by iris recognition systems is to be able to work with
people in motion, where the sensor is at an increasing distance (more than 1 m) from the …

Iris segmentation algorithms are of great significance in complete iris recognition systems,
and directly affect the iris verification and recognition results. However, the conventional iris …

Multimodal biometric systems have been widely applied in many real-world applications due
to its ability to deal with a number of significant limitations of unimodal biometric systems …

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 …

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 …

In many of the iris biometric applications plays a major role in tracking the gaze, detecting
fatigue, and predicting the age of a person, etc. that were built for human-computer …

Segmentation in iris biometrics deals with the localisation of inner and outer boundaries of
the iris and isolation of the region of interest (ROI) from the input eye image. The isolated …

Iris is an established modality in biometric recognition applications including consumer
electronics, e-commerce, border security, forensics, and de-duplication of identity at a …

The uncontrollable acquisition process limits the performance of iris recognition. In the
acquisition process, various inevitable factors, including eyes, devices, and environment …