A PROPOSED DATA MODEL FOR THE ENHANCED PROCESS OF ACQUISITION TESTED ON FINGERPRINT READERS

Abstract

Today, biometrics are increasingly used in everyday life. More and more devices have at least one sensor through which biometric samples are collected. The influence of the environment when taking biometric samples can be an important factor in the process of using biometric sensors. Also, the quality of the biometric sample can be affected by the contamination of the sensor or the biometric modality on which the sensor works. Evaluation of the quality of the biometric sample is an important part of the acquisition process. A data model has been developed that tracks performance sensitivity during biometric sample acquisition. In this paper, we present a data model that we tested on a multisensor biometric system with multiple fingerprint readers during the acquisition process. During the experiment, fingerprints were taken with different finger contaminations while controlling the environmental conditions under which the acquisition took place