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Proceedings Paper

Real-time signature verification using neural network algorithms to process optically extracted features
Author(s): Ned Francis O'Brien; Steven C. Gustafson
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Paper 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.

Paper Details

Date Published: 29 July 1994
PDF: 8 pages
Proc. SPIE 2234, Automatic Object Recognition IV, (29 July 1994); doi: 10.1117/12.181036
Show Author Affiliations
Ned Francis O'Brien, Univ. of Dayton (United States)
Steven C. Gustafson, Univ. of Dayton (United States)


Published in SPIE Proceedings Vol. 2234:
Automatic Object Recognition IV
Firooz A. Sadjadi, Editor(s)

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