Real-time signature verification using neural network algorithms to process optically extracted features

Ned Francis O'Brien; Steven C. Gustafson

doi:10.1117/12.181036

29 July 1994 Real-time signature verification using neural network algorithms to process optically extracted features

Ned Francis O'Brien, Steven C. Gustafson

Proceedings Volume 2234, Automatic Object Recognition IV; (1994) https://doi.org/10.1117/12.181036
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

A technique for handwritten signature verification is proposed which combines the pattern recognition abilities of neural networks with the feature extraction capabilities of optics. This two-part technique enables real time signature verification based upon power spectrum features and stored linear least squares and Gaussian radial basis function neural network weights.

Citation Download Citation

Ned Francis O'Brien and Steven C. Gustafson "Real-time signature verification using neural network algorithms to process optically extracted features", Proc. SPIE 2234, Automatic Object Recognition IV, (29 July 1994); https://doi.org/10.1117/12.181036

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