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Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel on-line signature verification system using the Singular Value Decomposition (SVD) numerical tool for signature classification and verification is presented. The proposed technique is based on the Singular Value Decomposition in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, so the effective dimensionality of A can be reduced. Having modeled the data glove signature through its r-principal subspace, signature authentication is performed by finding the angles between the different subspaces. A demonstration of the data glove is presented as an effective high-bandwidth data entry device for signature verification. This SVD-based signature verification technique is tested and its performance is shown to be able to recognize forgery signatures with a false acceptance rate of less than 1.2%.
Handwriting analysis, Pattern Recognition
Grant A. Ellis, Nidal S. Kamel, Shohel Sayeed, "Glove-Based Approach to Online Signature Verification", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 30, no. , pp. 1109-1113, June 2008, doi:10.1109/TPAMI.2008.32
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