1 January 2008 How the subject can improve fingerprint image quality
Mary Theofanos, Ross Michaels, Shahram Orandi, Brian Stanton, Nien-Fan Zhang
Author Affiliations +
Abstract
Traditionally, the biometric field has viewed the subject as a passive source of the biometric sample rather than as an interactive component of the biometric system. But fingerprint image quality is highly dependent on the human–computer interaction and usability considerations of the acquisition system. Those factors impacting the acquisition of high-quality images must be identified, and real-time feedback for subjects to ensure acceptable quality images must be integrated into fingerprint capture systems. We report on a usability study that examined the influence of instructional materials on the user (subject) performance of a 10-print slap acquisition process. In addition, we also investigated the relationship of pressure and image quality as a mechanism to provide real-time feedback to the subject. The usability study included 300 participants who received instructions and interacted with the scanner. How information is provided to the subject on interacting with the fingerprint device does indeed affect image quality. The pressure findings are less conclusive; there was no clear relationship between image quality and pressure that could be exploited for feedback to the subject. However, a minimum pressure was required to initiate our capture process.
©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)
Mary Theofanos, Ross Michaels, Shahram Orandi, Brian Stanton, and Nien-Fan Zhang "How the subject can improve fingerprint image quality," Journal of Electronic Imaging 17(1), 011007 (1 January 2008). https://doi.org/10.1117/1.2892681
Published: 1 January 2008
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image quality

Scanners

Video

Sensors

Biometrics

Light emitting diodes

Data modeling

RELATED CONTENT


Back to Top