A biometric system uniquely identifies and authenticates humans based on their physical or behavioural features. Iris recognition is one of the most reliable methods of biometric authentication that recognizes a person by pattern of the iris. No two irises are alike -not between identical twins, or even between the left eye and the right eye of the same person. The existing works on iris segmen...

Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address th...

Iris recognition is regarded as the most reliable and accurate biometric identification system. Most commercial iris recognition systems use patented algorithms developed by Daugman and these algorithms are able to produce perfect recognition rates. These algorithms are based on linear search methods which make the identification process extremely slow and also raise the false acceptance rate b...

This paper presents a complete iris identification system including three main stages: iris segmentation, signature extraction, and signature comparison. An accurate and robust pupil and iris segmentation process, taking into account eyelid occlusions, is first detailed and evaluated. Then, an original wavelet-packet-based signature extraction method and a novel identification approach, based o...

Iris pattern is the most reliable biometric in terms of recognition and identification performance. Nowadays iris recognition base on video is growing rapidly. In order to obtain a robust identification system, it requires a fast and accurate iris segmentation method to improve the recognition rate. In this paper we perform four optimizations to automates our previous segmentation method and re...

This special issue regards the recognition of degraded iris images acquired in visible wavelengths. During 2009 and 2010, the University of Beira Interior (Portugal) promoted two International evaluation initiatives about this subject, named Noisy Iris Challenge Evaluation (NICE) I and II. The first one focussed on the evaluation of iris segmentation strategies, considering that iris data acqui...

The growing concern with security and access control to places and sensitive information has contributed for the increased utilization of biometric systems. Biometry is the name given to the techniques used to recognize people automatically through physical and behavioural characteristics of the human body such as those found on the face, fingerprint, hand geometry, iris, signature or voice. Fr...

In noncooperative iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means eyelids and eyelashes occlusion, non uniform intensities, reflections, imperfect focus, and orientation among the others are to be considered. To cope with this situation a noncooperative iris segmentation algorithm based on numerically stable dire...

Volume 1, Issue 2 July-August 2012 Page 271 Abstract: Iris based biometric personal identification and Verification methods have gained much interest with an increasing emphasis on security. The proposed approach comprises of acquisition of Iris images, Iris Localization, Normalization and Quality Enhancement. Algorithms like Circular Hough transform, Canny Edge Detection, Gabor filters, Homoge...

Iris detection is a crucial part of an iris recognition system. One of the main issues in iris segmentation is coping with occlusions that happen due to eyelids and eyelashes. In this paper, only the lower part of the iris is utilized for recognition. Wavelet based texture features along with a mixed Hamming; harmonic mean distance classifier is used for identzjication. It is observed that rely...