Iris recognition is a biometric system for access control that uses the most unique characteristic of the human body, the iris employed in automated border crossings. This is Local binary pattern (LBP) is used for feature vectors extraction and Learning Vector Quantization (LVQ) performs classification. Here, matching is performed using the hamming distance of iris detections of matching. Iris ...

The present investigation was undertaken to determine if some of the components of exfoliation material in iris tissue were unique to exfoliation or were part of normal iris architecture. Eleven normal iris specimens and 10 exfoliative iris specimens were processed for cryoultramicrotomy and London resin white embedding. Immunogold electron microscopy was used to investigate the fine structural...

The paper proposes a new iris coding method based on Zak-Gabor wavelet packet transform. The essential component of the iris recognition methodology design is an effective adaptation of the transformation parameters that makes the coding sensitive to the frequencies characterizing ones eye. We thus propose to calculate the between-to-within class ratio of weakly correlated Zak-Gabor transformat...

Iris recognition has become a popular research in recent years due to its reliability and nearly perfect recognition rates. Iris recognition system has three main stages: image preprocessing, feature extraction and template matching. An innovative method is proposed to extract iris features based on texture analysis. Iris textures are analyzed to capture the discriminating frequency information...

The HIV-TB-associated immune reconstitution inflammatory syndrome (TB-IRIS) can complicate combined treatments for HIV-1 and TB. Little is known about tissue damage in TB-IRIS. Matrix metalloproteinases (MMPs) degrade components of the extracellular matrix and consequently may play a role in such immunopathology. Here we investigated the involvement of MMPs in TB-IRIS. We determined MMP transcr...

Iris recognition is the most accurate of the top three biometrics: fingerprints, facial recognition, and iris recognition. Iris recognition has a false accept rate of 1 in 1.2 million for one eye (1 in 1.44 trillion for two eyes) regardless of database size [1]. Iris recognition is the easiest one among biometrics related with the eye. It works with simple CCD camera and does not need direct co...

High resolution images not only provide high recognition rate but also useful in safeguarding the iris recognition system from fake iris attack. To safeguard the iris recognition system against fake irises, one of the very popular technique is to detect the change in pupil size due to change in illumination. Many of existing methods assume that iris and pupil are circular or elliptical in natur...

BACKGROUND Tuberculosis immune reconstitution inflammatory syndrome (IRIS) is a common cause of deterioration in human immunodeficiency virus (HIV)-infected patients receiving tuberculosis treatment after starting antiretroviral therapy (ART). Potentially life-threatening neurological involvement occurs frequently and has been suggested as a reason to defer ART. METHODS We conducted a prospec...

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...

Iris segmentation is almost the most challenging part in iris recognition. Several robust algorithms in the recognition part have been developed in literature yet. In this paper, we focus on an efficient approach for iris segmentation. The main purposes are to improve accuracy and to reduce computational time of iris localization. Briefly, this approach tries to explore regions of interests (RO...