Neural network signature verification using Haar wavelet and Fourier transforms
Daniel K. R. McCormack, B. Malcolm Brown, John F. Pedersen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
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.