On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
FVC2000: Fingerprint Verification Competition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Gray-Scale Minutiae Detection In Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
FRIDGE: An Interactive Code Generation Environment for HW/SW CoDesign
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Filterbank-based fingerprint matching
IEEE Transactions on Image Processing
Fast fingerprint verification using subregions of fingerprint images
IEEE Transactions on Circuits and Systems for Video Technology
Efficient fingerprint-based user authentication for embedded systems
Proceedings of the 42nd annual Design Automation Conference
Secure fingerprint matching with external registration
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Hi-index | 0.00 |
Fingerprint sensors are getting small enough to be included in mobile devices to enable fingerprint verification be employed as an authentication tool when using the mobile devices for secure transactions. Fingerprint verification, however, is a computing intensive technology that requires a lot of floating-point computation. Unfortunately, the embedded processors in most mobile devices do not support floating-point hardware. In this paper, we present the implementation of a fingerprint verification process in an embedded system environment based the StrongArm processor and the embedded Linux operating system. The success of the implementation relies on the use of a fixed-point arithmetic only. The fingerprint verification component, the fixed-point component as well as the technique employed to pair up the two components are described in details. In particular, we estimated the required precisions in the fixed-point representations before conducting experiments. Through our results, we further show that not only the fixed-point implementation achieves the goal of significant speed improvement but is almost as reliable as the floating-point counterparts.