Title :
Comparison of face image quality metrics: Electronic and legacy mug shots
Author :
O´Connor, Kevin ; Hales, Gregory ; Hight, Jonathon ; Modi, Shimon ; Elliott, Stephen
Author_Institution :
Dept. of Technol., Leadership & Innovation, Purdue Univ., West Lafayette, IN, USA
Abstract :
Automated face recognition offers an effective method for identifying individuals. Face images have been used in a number of different applications, including driver´s licenses, passports and identification cards. To provide some form of standardization for photographs in these applications, ISO / IEC JTC 1 SC 37 have developed standardized data interchange formats to promote interoperability. There are many different publically available face databases available to the research community that are used to advance the field of face recognition algorithms, amongst other uses. In this paper, we examine how an existing database that has been used extensively in research (FERET) compares with two operational data sets with respect to some of the metrics outlined in the standard ISO / IEC 19794-5. The goals of this research are to provide the community with a comparison of a baseline data set and to compare this baseline to a photographic data set that has been scanned in from mug-shot photographs, as well as a data set of digitally captured photographs. It is hoped that this information will provide Face Recognition System (FRS) developers some guidance on the characteristics of operationally collected data sets versus a controlled-collection database.
Keywords :
IEC standards; ISO standards; digital photography; electronic data interchange; face recognition; open systems; standardisation; visual databases; ISO/IEC 19794-5; ISO/IEC JTC 1 SC 37; automated face recognition; controlled-collection database; data interchange formats; digitally captured photographs; driver´s licenses; electronic shots; face image databases; face image quality metrics; identification cards; interoperability; legacy mug shots; passports; photographic data set; standardization; Databases; Face; Face recognition; Feature extraction; Image quality; Lighting; Measurement; biometrics; face recognition; image quality; law enforcement;
Conference_Titel :
Computational Intelligence in Biometrics and Identity Management (CIBIM), 2011 IEEE Workshop on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9899-4
DOI :
10.1109/CIBIM.2011.5949219