Recently, iris recognition techniques have achieved great performance in identification.
Among authentication techniques, iris recognition systems have received attention very …

Pupil detection in a human eyeimage or video plays a key role in many applications such as
eye-tracking, diabetic retinopathy screening, smart homes, iris recognition, etc. Literature …

Iris images captured in non-cooperative environments often suffer from adverse noise, which
challenges many existing iris segmentation methods. To address this problem, this paper …

Cataract surgery remains the only definitive treatment for visually significant cataracts, which
are a major cause of preventable blindness worldwide. Successful performance of cataract …

The very high recognition accuracy of iris-based biometric systems and the increasing
distribution of high-resolution personal images on websites and social media are creating …

People upload daily a huge number of portrait face pictures on websites and social media,
which can be processed using biometric systems based on the face characteristics to …

Pupil segmentation is a first and important topic of iris recognition, identity recognition and
eye movement information extraction for mental analysis. However, due to the negative …

This paper proposes a novel, lightweight deep convolutional neural network specifically
designed for iris segmentation of noisy images acquired by mobile devices. Unlike previous …

Iris segmentation plays a critical role in the iris biometric systems. It has two modules: iris
localization and noise detection. The first module demarcates the actual iris' inner and outer …

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