Forgery detection in dynamic signature verification by entailing principal component analysis

Sayeed, S. and Andrews, S. and Besar, R. and Kiong, L.C. (2008) Forgery detection in dynamic signature verification by entailing principal component analysis. Discrete Dynamics in Nature and Society, 2007. ISSN 1026-0226,


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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.

Item Type: Article
Uncontrolled Keywords: Forgery detection; input signals; artificial intelligence; computer science
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science & Information Technology > Department of Artificial Intelligence
Depositing User: Miss Nur Jannatul Adnin Ahmad Shafawi
Date Deposited: 21 Mar 2013 01:56
Last Modified: 21 Mar 2013 01:56

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