A New Hand Based Biometric Modality & An Automated Authentication System

With increased adoption of smartphones, security has become important like never before. Smartphones store confidential information and carry out sensitive financial transactions. Biometric sensors such as fingerprint scanners are built in to smartphones to cater to security concerns. However, due to limited size of smartphone, miniaturised sensors are used to capture the biometric data from the user. Other hand based biometric modalities like hand veins and finger veins need specialised thermal/IR sensors which add to the overall cost of the system. In this paper, we introduce a new hand based biometric modality called Fistprint.  Fistprints can be captured using digital camera available in any smartphone. In this work, our contributions are: i) we propose a new non-touch and non-invasive hand based biometric modality called fistprint. Fistprint contains many distinctive elements such as fist shape, fist size, fingers shape and size, knuckles, finger nails, palm crease/wrinkle lines etc. ii) Prepare fistprint DB for the first time. We collected fistprint information of twenty individuals - both males and females aged from 23 years to 45 years of age. Four images of each hand fist (total 160 images) were taken for this purpose. iii) Propose Fistprint Automatic Authentication SysTem (FAAST). iv) Implement FAAST system on Samsung Galaxy smartphone running Android and server side on a windows machine and validate the effectiveness of the proposed modality. The experimental results show the effectiveness of fistprint as a biometric with GAR of 97.5 % at 1.0% FAR

Development of a real time fingerprint authentication/identification system for students’ record

Human fingerprints are rich in details called minutiae, which can be used as identification marks for fingerprint verification. This paper presents the development of a real time fingerprint authentication system built as an application of an optical fingerprint scanner (“SecuGen”) and its free software developers’ kit (SDK). To achieve good minutiae extraction in fingerprints with varying quality, Gabor filter was designed and incorporated for image enhancement. The matching algorithm used in the SecuGen’s SDK is capable of finding the correspondences between input minutia pattern and the stored template minutia pattern without resorting to exhaustive search. Gabor filter is used to enhance the unique features of the fingerprint before these features are compared for authentication and recognition of a person. The result shows the improvement in accuracy level of the fingerprint authentication system when the enhanced (filtered) image is used as compared to when a noisy image is used.Keywords: Biometrics; Fingerprint Recognition; Gabor filters; Fingerprint Authentication/Verification; Fingerprint Identificatio