by Xiaomei Liu Biometric verification systems employing images of the iris are claimed to be extremely accurate, yielding no false accepts at any reasonable false reject rate. However, there are few if any large scale experimental evaluations on public iris datasets reported in the literature. We have collected an iris image dataset of over 25,000 iris images from over 300 persons (over 600 iri...

The traditional iris recognition systems require equal high quality human iris images. A cheap image acquisition system has difficulty in capturing equal high quality iris images. This paper describes a new feature representation method for iris recognition robust to noises. The disc-shaped iris image is first convolved with a low pass filter along the radial direction. Then, the radially smoot...

Custom JPEG quantisation matrices are proposed to be used in the context of compressing iris polar images within iris recognition. These matrices are obtained by employing a Genetic algorithm for the corresponding optimisation. Superior matching results in iris recognition in terms of average Hamming distance and improved ROC are found as compared to the use of the default JPEG quantisation table.

The interface of computer technologies and biology is having a huge impact on society. Human recognition research projects promises new life to many security-consulting. Iris recognition is considered to be the most reliable biometric authentication system. Very few iris recognition algorithms were commercialized. We implemented a system that process two different kinds of iris databases: CASIA...

In general, the iris recognition systems have used the wavelet transform as feature extraction techniques. Since the wavelet transform does not have the shift-invariant property, the iris features are inconsistently extracted due to the eye image rotation and the inexact iris localization. In this paper, a novel method to extract features is proposed for iris recognition system. Two types of fe...

Iris Recognition is considered as one of the best Biometric methods used for human identification and verification, because of its unique feature that differ from one person to another, and its importance in the security field. We proposed an algorithm using a system based on Local Binary Pattern and histogram approaches for feature extraction, and Linear Vector Quantization classifier for clas...

Pair of iris recognition is very effective for person identification due to the iris unique features and the protection of the iris from the environment and aging. In addition it is well suitable to embark upon accidental or ophthalmological disease issue. This paper presents a simple methodology for pre-processing pair of iris images which means both left and right eye of human(instead of eith...

Biometric methods designed for the identification of individuals are nowadays increasingly being used in the routine tasks like medical check-up, security etc. These powerful techniques are slowly replacing the less secure ID or password methods for user authentication. Iris recognition is especially attractive due to the high degree of entropy per unit area of the iris, as well as the stabilit...

Iris recognition is one of the challenging problems inhuman computer interaction. An automated iris recognition system requires an efficient method for classification of iris region in the face sequence, extraction of iris features, and construction of classification model. In recent years, Neural Networks (NN) has demonstrated excellent performance in a variety of classification problems. In t...