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Contactless Print Capture |
Keywords: fingerprints, palm prints, hand geometry, contactless capture, friction ridge capture
Citation:
Abstract
The increased demand for tighter border and
building security has renewed public interest in biometric identification
and verification systems. With fingerprint recognition
being socially stigmatized, hand geometry-based recognizers
have emerged as niche solutions. However, systems currently
available in the marketplace require direct contact with the
device, raising, among others, significant hygiene concerns. In
this paper we introduce a novel approach to hand geometrybased
identification. The proposed method employs Active
Appearance Models to track the hand inside the capture device
and to extract geometry features for identification. The AAM
fitting algorithm runs faster than real-time, enabling robust
system performance. In experiments on a small-scale database
of hand images, the accuracy of our system exceeds 90% using
as little as five features.
Ralph Gross, Yiheng Li,
Latanya Sweeney,
Xiaoqian Jiang, Wanhong Xu, and Daniel Yurovsky.
Robust Hand Geometry Measurements for Person Identification using
Active Appearance Models.
IEEE Conference on Biometrics (BTAS), Washington, DC, September 2007.
(PDF).
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