Biometric Standards, Performance, and Assurance Laboratory

Department of Industrial Technology

ISO/IEC JTC1 SC37 Conceptual Biometric Model

Researchers at Purdue's Biometric Standards, Performance and Assurance Laboratory examine the effect of sensor dependent variations and distortions, and characteristics of the sensor on the interoperability matching error rates of minutiae based fingerprint recognition systems. The problem space affecting error rates of fingerprint datasets is vast - every subsystem of a fingerprint recognition system has an influence on performance of a fingerprint dataset. The end objective of this research is to provide greater insight into the effect of a fingerprint dataset acquired from various sensors on performance measured in terms of error rates like false non match rates (FNMR) and false match rates (FMR). The outcome of this research will be useful in designing matching algorithms which are better at handling fingerprint images from various sensors.

For more about this research, please go to the fingerprint sensor interoperability research area.