Topic
Iris recognition
About: Iris recognition is a research topic. Over the lifetime, 6411 publications have been published within this topic receiving 110395 citations.
Papers published on a yearly basis
Papers
More filters
Patent•
10 Oct 1992
TL;DR: In this article, the sign of the projection of many different parts of the iris onto these filters determines each bit in an iris code, and the similarity metric (Hamming distance) is computed from the XOR of any two iris codes.
Abstract: Image analysis algorithms find the iris in a live video image (10) of a person's face, and encode its texture into an 'iris code' (24). Iris texture is extracted from the image at multiple scales of analysis by a self-similar set of quadrature bandpass filters defined in a dimensionless polar coordinate system. The sign of the projection of many different parts of the iris onto these filters determines each bit in an iris code. Comparisons between codes are readily implemented by the Exclusive-OR (XOR) logical operation. Pattern recognition is achieved by combining signal processing methods with statistical decision theory, leading to a statistical test of independence based on a similarity metric (Hamming distance) (26) that is computed from the XOR of any two iris codes. This measure positively establishes, confirms, or disconfirms, the identity of any individual (28). It also generates an objective confidence level (30) associated with the identification decision.
988 citations
TL;DR: This survey covers the historical development and current state of the art in image understanding for iris biometrics and suggests a short list of recommended readings for someone new to the field to quickly grasp the big picture of irisBiometrics.
933 citations
TL;DR: This paper provides an ''ex cursus'' of recent face recognition research trends in 2D imagery and 3D model based algorithms and proposes possible future directions.
931 citations
01 Jan 2003
TL;DR: The work presented in this thesis involved developing an ‘open-source’ iris recognition system in order to verify both the uniqueness of the human iris and also its performance as a biometric.
Abstract: A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. Most commercial iris recognition systems use patented algorithms developed by Daugman, and these algorithms are able to produce perfect recognition rates. However, published results have usually been produced under favourable conditions, and there have been no independent trials of the technology. The work presented in this thesis involved developing an ‘open-source’ iris recognition system in order to verify both the uniqueness of the human iris and also its performance as a biometric. For determining the recognition performance of the system two databases of digitised greyscale eye images were used. The iris recognition system consists of an automatic segmentation system that is based on the Hough transform, and is able to localise the circular iris and pupil region, occluding eyelids and eyelashes, and reflections. The extracted iris region was then normalised into a rectangular block with constant dimensions to account for imaging inconsistencies. Finally, the phase data from 1D Log-Gabor filters was extracted and quantised to four levels to encode the unique pattern of the iris into a bit-wise biometric template. The Hamming distance was employed for classification of iris templates, and two templates were found to match if a test of statistical independence was failed. The system performed with perfect recognition on a set of 75 eye images; however, tests on another set of 624 images resulted in false accept and false reject rates of 0.005% and 0.238% respectively. Therefore, iris recognition is shown to be a reliable and accurate biometric technology.
908 citations
Patent•
04 Feb 1986
TL;DR: In this paper, an image of the iris and pupil is compared with stored image information for identification, which is previously obtained from an eye, the pupil of which was similarly brought to the same predetermined size.
Abstract: Methods and apparatus for identifying an eye, especially a human eye (10), on the basis of the visible features of the iris (20) and pupil (30). The eye is first illuminated until the pupil reaches a predetermined size, at which an image of the iris and pupil is obtained. This image is then compared with stored image information for identification. The stored image information is previously obtained from an eye, the pupil of which was similarly brought to the same predetermined size. The illumination of the iris may include oblique illumination from several positions around the circumference of the iris. The illumination from each position may be relatively monochromatic, so that the resulting shadow will lack the color of the light source (172) at that position providing better contrast for elevation-dependent features. A system for performing iris recognition (100) may include a processor (190) which controls an illumination control circuit (170) and a camera (180) to obtain images at several predetermined sizes of the pupil.
666 citations