Implications of the advanced mini-max (AMM) classifier on non-cooperative standoff biometrics

Kenneth A. Byrd; Harold Szu; Mohamed F. Chouikha

doi:10.1117/12.820832

19 March 2009 Implications of the advanced mini-max (AMM) classifier on non-cooperative standoff biometrics

Kenneth A. Byrd, Harold Szu, Mohamed F. Chouikha

Proceedings Volume 7343, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII; 734315 (2009) https://doi.org/10.1117/12.820832
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

AMM classification is an advanced version of the typical nearest neighbor classifier that allows one to minimize interclass dispersion while at the same time, maximizing intraclass separation. A technique based on the simple orthogonal feature space of Pentland eigenfaces, the combination of these two embodiments will become essential components to a non-cooperative standoff biometric system for military, medical and homeland security applications. The incorporation of robotic assistance further pushes the frontiers of possible surveillance and authentication that can be realized with such a system. The ability to perform out of the line of sight (OLS)-based surveillance adds an additional dimension, and thus novelty, to the already expanding methods to acquire and process environment-specific data.

Citation Download Citation

Kenneth A. Byrd, Harold Szu, and Mohamed F. Chouikha "Implications of the advanced mini-max (AMM) classifier on non-cooperative standoff biometrics", Proc. SPIE 7343, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII, 734315 (19 March 2009); https://doi.org/10.1117/12.820832

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available