Quality in face and iris research ensemble (Q-FIRE)

Identification of individuals using biometric information has found great success in many security and law enforcement applications. Up until the present time, most research in the field has been focused on ideal conditions and most available databases are constructed in these ideal conditions. There has been a growing interest in the perfection of these technologies at a distance and in less than ideal conditions, i.e. low lighting, out-of-focus blur, off angles, etc. This paper presents a dataset consisting of face and iris videos obtained at distances of 5 to 25 feet and in conditions of varying quality. The purpose of this database is to set a standard for quality measurement in face and iris data and to provide a means for analyzing biométrie systems in less than ideal conditions. The structure of the dataset as well as a quantified metric for quality measurement based on a 25 subject subset of the dataset is presented.