Discrete Dynamics in Nature and Society
Volume 2007 (2007), Article ID 70756, 8 pages
Research Article

Forgery Detection in Dynamic Signature Verification by Entailing Principal Component Analysis

Shohel Sayeed,1 S. Andrews,1 Rosli Besar,2 and Loo Chu Kiong2

1Faculty of Information Science and Technology, Multimedia University, Melaka 75450, Malaysia
2Faculty of Engineering and Technology, Multimedia University, Melaka 75450, Malaysia

Received 21 July 2007; Accepted 6 October 2007

Copyright © 2007 Shohel Sayeed et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The critical analysis of the data glove-based signature identification and forgery detection system emphasizes the essentiality of noise-free signals for input. Lucid inputs are expected for the accuracy enhancement and performance. The raw signals that are captured using 14- and 5-electrode data gloves for this purpose have a noisy and voluminous nature. Reduction of electrodes may reduce the volume but it may also reduce the efficiency of the system. The principal component analysis (PCA) technique has been used for this purpose to condense the volume and enrich the operational data by noise reduction without affecting the efficiency. The advantage of increased discernment in between the original and forged signatures using 14-electrode glove over 5-electrode glove has been discussed here and proved by experiments with many subjects. Calculation of the sum of mean squares of Euclidean distance has been used to project the advantage of our proposed method. 3.1% and 7.5% of equal error rates for 14 and 5 channels further reiterate the effectiveness of this technique.