7,167 research outputs found
Feature-domain super-resolution framework for Gabor-based face and iris recognition
The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics
Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography
Several recent works have proposed and implemented cryptography as a means to
preserve privacy and security of patients health data. Nevertheless, the
weakest point of electronic health record (EHR) systems that relied on these
cryptographic schemes is key management. Thus, this paper presents the
development of privacy and security system for cryptography-based-EHR by taking
advantage of the uniqueness of fingerprint and iris characteristic features to
secure cryptographic keys in a bio-cryptography framework. The results of the
system evaluation showed significant improvements in terms of time efficiency
of this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy
commitment demonstrated false acceptance rate (FAR) of 0%, which reduces the
likelihood of imposters gaining successful access to the keys protecting
patients protected health information. This result also justifies the
feasibility of implementing fuzzy key binding scheme in real applications,
especially fuzzy vault which demonstrated a better performance during key
reconstruction
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