Score level fusion approach in dynamic signature verification based on hybrid wavelet-Fourier transform

In this paper, we propose a dynamic signature verification system which integrates hybrid of Discrete Wavelet Transform and Discrete Fourier Transform (DWT-DFT) for feature extraction. In feature matching, Euclidean distance and Enveloped Euclidean distance (EED) (a variant of Euclidean distance) are used. Distances of features are fused into a final score value and used to classify whether a genuine or a forgery signature. A benchmark database, SVC2004 which compose of Task 1 dataset and Task 2 dataset validate the effectiveness of this proposed system. Experimental results reveal a 7.08% EER for skilled forgeries and 2.37% EER of random forgeries in Task 1 dataset; and 8.61% EER for skilled forgeries and 2.05% EER for random forgeries in Task 2 dataset.