Iris feature extraction: a survey

Biometric as a technology has been proved to be a reliable means of enforcing constraint in a security sensitiveenvironment. Among the biometric technologies, iris recognition system is highly accurate and reliable becauseof their stable characteristics throughout lifetime. Iris recognition is one of the biometric identification thatemploys pattern recognition technology with the use of high resolution camera. Iris recognition consist of manysections among which feature extraction is an important stage. Extraction of iris features is very important andmust be successfully carried out before iris signature is stored as a template. This paper gives a comprehensivereview of different fundamental iris feature extraction methods, and some other methods available in literatures.It also gives a summarised form of performance accuracy of available algorithms. This establishes a platform onwhich future research on iris feature extraction algorithm(s) as a component of iris recognition system can bebased.Keywords: biometric authentication, false acceptance rate (FAR), false rejection rate (FRR), feature extraction,iris recognition system

A framework for biometric recognition using non-ideal iris and face

Off-angle iris images are often captured in a non-cooperative environment. The distortion of the iris or pupil can decrease the segmentation quality as well as the data extracted thereafter. Moreover, iris with an off-angle of more than 30° can have non-recoverable features since the boundary cannot be properly localized. This usually becomes a factor of limited discriminant ability of the biometric features. Limitations also come from the noisy data arisen due to image burst, background error, or inappropriate camera pixel noise. To address the issues above, the aim of this study is to develop a framework which: (1) to improve the non-circular boundary localization, (2) to overcome the lost features, and (3) to detect and minimize the error caused by noisy data. Non-circular boundary issue is addressed through a combination of geometric calibration and direct least square ellipse that can geometrically restore, adjust, and scale up the distortion of circular shape to ellipse fitting. Further improvement comes in the form of an extraction method that combines Haar Wavelet and Neural Network to transform the iris features into wavelet coefficient representative of the relevant iris data. The non-recoverable features problem is resolved by proposing Weighted Score Level Fusion which integrates face and iris biometrics. This enhancement is done to give extra distinctive information to increase authentication accuracy rate. As for the noisy data issues, a modified Reed Solomon codes with error correction capability is proposed to decrease intra-class variations by eliminating the differences between enrollment and verification templates. The key contribution of this research is a new unified framework for high performance multimodal biometric recognition system. The framework has been tested with WVU, UBIRIS v.2, UTMIFM, ORL datasets, and achieved more than 99.8% accuracy compared to other existing methods

Generation of Cryptographic Key from Eye Biometric Features

Hlavním tématem práce je vytvoření vzorců pro množství informační entropie v biometrických vlastnostech duhovky a sítnice. Toto odvětví je zatím v těchto biometrikách neprostudováno, proto se diplomová práce snaží zahájit výzkum tímto směrem. V práci jsou dále zmíněny historické souvislosti z oboru bezpečnosti a identifikace podle biometrických vlastností člověka, s případným přesahem pro využití v biometrikách duhovky a sítnice. Podrobně je probrán Daugmanův algoritmus pro převod snímku duhovky na binární kód, který může být využit jako kryptografický klíč. Součástí práce je i aplikace, která právě zmíněný převod provádí.The main topic of the thesis is creation of formulas for the amount of information entropy in biometric characteristics of iris and retina. This field of science in biometrics named above is unstudied yet, so the thesis tries to initiate research in this direction. The thesis also discusses the historical context of security and identification fields according to biometric characteristics of a human being with an overlap for potential usage in biometrics of iris and retina. The Daugman’s algorithm for converting iris image into the binary code which can be used as a cryptographic key is discussed in detail. An application implementing this conversion is also a part of the thesis.