This study investigates various feature selection techniques for face recognition. Biometric based authentication system protects access to resources and has gained importance, because of their reliable, invariant and discriminating features. An automated biometric system is based on physiological or behavioral human characteristics for protected access. Biometric trait such as palmprint, iris,...

In this study, two techniques that can improve the authentication process are examined: (i) multiple samples and (ii) multiple biometric sources. We propose the fusion of multiple samples obtained from multiple biometric sources at the score level. By using the average operator, both the theoretical and empirical results show that integrating as many samples and as many biometric sources as pos...

Data Collection Poster Instruction Measurement & Framework The purpose of this study is to examine the impact that training methods have on biometric usability and performance results. Previous research has shown that biometric devices have usability, ergonomic, and design issues which have an impact on the performance of the entire biometric system. This research is looking specifically at the...

Two sources of weak biometric data are investigated for the development of user identification models. A probabilistic neural network model is created from keystroke digraph features extracted from raw typing data. A second model is developed from scan-path features extracted from raw eye-tracking data. A third model is created from a combination of features from the two biometric sources. Expe...

Biometric systems are developed in order to replace traditional authentication. However, protecting the stored templates is considered as one of the critical steps in designing a secure biometric system. When biometric data is compromised, unlike passwords, it can’t be revoked. One methodology for biometric template protection is ‘Biometric Cryptosystem’. Biometric cryptosystems benefit from bo...

A keystroke biometric classification system traditionally used on data captured from physical keyboards associated with laptops and personal computers, was extended to evaluate biometric data extracted from mobile devices. The results were compared to the results of similar studies utilizing the same data inputs. Additional results were extracted; including results tied to features native to mo...

This review paper introduces the concepts of multimodal biometrics that integrates two or more biometric identifiers and takes advantage of the capabilities of each biometric to provide greater performance and higher reliability. It also discusses various levels of fusion, the importance of fusion at the feature level and a comparative study using different algorithms for performance analysis.