This paper studies the iris recognition problem in the degraded iris images captured in non-ideal imaging conditions. In these circumstances iris recognition becomes challenging because of noisy factors such as the off-axis imaging, pose variation, image blurring, illumination change, occlusion, specular highlights and noise. We introduce a robust algorithm based on the Random Sample Consensus ...

An authentic personal identification infrastructure is required to control the access in order to secure areas or materials. Biometric technology is based on physiological or behavioral characteristics of a human body. Iris recognition system consists of image acquisition, localization, normalization, features extraction and encoding, and classification. Iris images are downloaded from CASIA Ir...

The orientation of iris texture will influence the iris recognition rate and the 2 dimensional Gabor filters (2-D Gabor) has better selectivity in orientation and frequency, so the multi-scales and multi directions 2-D Gabor filters can be used to extract the iris features. But there are many shortcomings such as long extraction feature time and high feature dimensions to use the traditional 2-...

Multispectral Iris Recognition Analysis: Techniques and Evaluation by Christopher K. Boyce Master of Science in Electrical Engineering West Virginia University Lawrence Hornak, Ph.D., Chair Arun Ross, Ph.D. (Co-chair) This thesis explores the benefits of using multispectral iris information acquired using a narrow-band multispectral imaging system. Commercial iris recognition systems typically ...

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...

Uniqueness of iris patterns among individuals has resulted in the ubiquity of iris recognition systems in virtual and physical spaces, at high security facilities around the globe. Traditional methods of acquiring iris patterns in commercial systems scan the iris when an individual is at a predetermined location in front of the scanner. Most state-of-the-art techniques for unconstrained iris ac...

Iris recognition from surveillance-type imagery is an active research topic in biometrics. However, iris identification in unconstrained conditions raises many proplems related to localization and alignment, and typically leads to degraded recognition rates. While development has mainly focused on more robust preprocessing, this work highlights the possibility to account for distortions at matc...

Iris Recognition Systems are ocularbased biometric devices used primarily for security reasons. The complexity and the randomness of the Iris, amongst various other factors, ensure that this biometric system is inarguably an exact and reliable method of identification. The algorithm is responsible for automatic localization and segmentation of boundaries using circular Hough Transform, noise re...

In this paper, a robust method is developed to locate the irises of both eyes. The method doesn’t put any restrictions on the background. The method is based on the AdaBoost algorithm for face and eye candidate points detection. Candidate points are tuned such that two candidate points are exactly in the centers of the irises. Mean crossing function and convolution template are proposed to filt...