Neural network signature verification using Haar wavelet and Fourier transforms

Daniel K. R. McCormack; B. Malcom Brown; John F. Pedersen

doi:10.1117/12.150284

6 August 1993 Neural network signature verification using Haar wavelet and Fourier transforms

Daniel K. R. McCormack, B. Malcom Brown, John F. Pedersen

Proceedings Volume 2064, Machine Vision Applications, Architectures, and Systems Integration II; (1993) https://doi.org/10.1117/12.150284
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

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.

Citation Download Citation

Daniel K. R. McCormack, B. Malcom Brown, and John F. Pedersen "Neural network signature verification using Haar wavelet and Fourier transforms", Proc. SPIE 2064, Machine Vision Applications, Architectures, and Systems Integration II, (6 August 1993); https://doi.org/10.1117/12.150284

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