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Online Signature Verification and Recognition: An Approach Based on Symbolic Representation
June 2009 (vol. 31 no. 6)
pp. 1059-1073
ASCII Text
x 
 
D.S. Guru, H.N. Prakash, "Online Signature Verification and Recognition: An Approach Based on Symbolic Representation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 6, pp. 1059-1073, June, 2009.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2008.302,
author = {D.S. Guru and H.N. Prakash},
title = {Online Signature Verification and Recognition: An Approach Based on Symbolic Representation},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {31},
number = {6},
issn = {0162-8828},
year = {2009},
pages = {1059-1073},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.302},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Online Signature Verification and Recognition: An Approach Based on Symbolic Representation
IS - 6
SN - 0162-8828
SP1059
EP1073
EPD - 1059-1073
A1 - D.S. Guru,
A1 - H.N. Prakash,
PY - 2009
KW - On-line signature verification
KW - On-line signature recognition
KW - Symbolic features
KW - Interval valued features
KW - Writer dependent threshold
VL - 31
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
D.S. Guru, University of Mysore, Mysore
H.N. Prakash, University of Mysore, Mysore
In this paper, we propose a new method of representing on-line signatures by interval valued symbolic features. Global features of on-line signatures are used to form an interval valued feature vectors. Methods for signature verification and recognition based on the symbolic representation are also proposed. We exploit the notions of writer dependent threshold and introduce the concept of feature dependent threshold to achieve a significant reduction in equal error rate. Several experiments are conducted to demonstrate the ability of the proposed scheme in discriminating the genuine signatures from the forgeries. We investigate the feasibility of the proposed representation scheme for signature verification and also signature recognition using all 16500 signatures from 330 individuals of the MCYT bimodal biometric database. Further, extensive experimentations are conducted to evaluate the performance of the proposed methods by projecting features onto Eigenspace and Fisherspace. Unlike other existing signature verification methods, the proposed method is simple and efficient. The results of the experimentations reveal that the proposed scheme outperforms several other existing verification methods including the state-of-the-art method for signature verification.

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Index Terms:
On-line signature verification, On-line signature recognition, Symbolic features, Interval valued features, Writer dependent threshold
Citation:
D.S. Guru, H.N. Prakash, "Online Signature Verification and Recognition: An Approach Based on Symbolic Representation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 6, pp. 1059-1073, June 2009, doi:10.1109/TPAMI.2008.302
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