KEYWORDS: Laser Doppler velocimetry, Biometrics, Data modeling, Time-frequency analysis, Data fusion, Electrocardiography, Doppler effect, Performance modeling, Signal processing, Information fusion
A novel approach using mechanical physiological activity as a biometric marker is described. Laser Doppler Vibrometry
is used to sense activity in the region of the carotid artery, related to arterial wall movements associated
with the central blood pressure pulse. The non-contact basis of the LDV method has several potential benefits in
terms of the associated non-intrusiveness. Several methods are proposed that use the temporal and/or spectral
information in the signal to assess biometric performance both on an intra-session basis, and on an intersession
basis involving testing repeated after delays of 1 week to 6 months. A waveform decomposition method that
utilizes principal component analysis is used to model the signal in the time domain. Authentication testing
for this approach produces an equal-error rate of 0.5% for intra-session testing. However, performance degrades
substantially for inter-session testing, requiring a more robust approach to modeling. Improved performance
is obtained using techniques based on time-frequency decomposition, incorporating a method for extracting informative
components. Biometric fusion methods including data fusion and information fusion are applied in
multi-session data training model. As currently implemented, this approach yields an inter-session equal-error
rate of 9%.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.