Share Email Print
cover

Proceedings Paper

Neural network signature verification using Haar wavelet and Fourier transforms
Author(s): Daniel K. R. McCormack; B. Malcom Brown; John F. Pedersen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper discusses the use of neural network's for handwritten signature verification using the Fourier and Haar wavelet transforms as methods of encoding signature images. Results will be presented that discuss a neural network's ability to generalize to unseen signatures using wavelet encoded training data. These results will be discussed with reference to both Backpropagation networks and Cascade-Correlation networks. Backpropagation and Cascade- Correlation networks are used to compare and contrast the generalization ability of Haar wavelet and Fourier transform encoded signature data.

Paper Details

Date Published: 6 August 1993
PDF: 12 pages
Proc. SPIE 2064, Machine Vision Applications, Architectures, and Systems Integration II, (6 August 1993); doi: 10.1117/12.150284
Show Author Affiliations
Daniel K. R. McCormack, Univ. of Wales College Cardiff (United Kingdom)
B. Malcom Brown, Univ. of Wales College Cardiff (United Kingdom)
John F. Pedersen, Univ. of South Florida (United States)


Published in SPIE Proceedings Vol. 2064:
Machine Vision Applications, Architectures, and Systems Integration II
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

© SPIE. Terms of Use
Back to Top