Dynamic handwritten signature verification based on statistical quantization mechanism

Song Ong Thian; How Khoh Wee; Beng Jin Teoh Andrew

doi:10.1109/ICCET.2009.128

Dynamic handwritten signature verification based on statistical quantization mechanism

Song Ong Thian, How Khoh Wee, Beng Jin Teoh Andrew

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

16 Citations (Scopus)

Abstract

Online handwritten signature has been widely used for identity verification. However, it suffers from large intra-class variation problem as individual's signature may deviate from time to time due to variations in signing position, signature size, writing surface, and other factors. In addition, signatures are easier to forge than other biometrics and this leads to random and skilled forgeries issues. In this paper, we propose a novel Statistical Quantization Mechanism (SQM) to suppress the intra-class variation in signature features and thus discriminate the difference between genuine signature and its forgery. Experimental results show the proposed method is feasible in practice.

Original language	English
Title of host publication	Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009
Pages	312-316
Number of pages	5
DOIs	https://doi.org/10.1109/ICCET.2009.128
Publication status	Published - 2009

Publication series

Name	Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009
Volume	2

All Science Journal Classification (ASJC) codes

Computer Science Applications
Software

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10.1109/ICCET.2009.128

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Thian, S. O., Wee, H. K., & Andrew, B. J. T. (2009). Dynamic handwritten signature verification based on statistical quantization mechanism. In Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009 (pp. 312-316). [4769612] (Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009; Vol. 2). https://doi.org/10.1109/ICCET.2009.128

@inproceedings{dd31ee857bd247d9ac795d1d0d3938a0,

title = "Dynamic handwritten signature verification based on statistical quantization mechanism",

abstract = "Online handwritten signature has been widely used for identity verification. However, it suffers from large intra-class variation problem as individual's signature may deviate from time to time due to variations in signing position, signature size, writing surface, and other factors. In addition, signatures are easier to forge than other biometrics and this leads to random and skilled forgeries issues. In this paper, we propose a novel Statistical Quantization Mechanism (SQM) to suppress the intra-class variation in signature features and thus discriminate the difference between genuine signature and its forgery. Experimental results show the proposed method is feasible in practice.",

author = "Thian, {Song Ong} and Wee, {How Khoh} and Andrew, {Beng Jin Teoh}",

year = "2009",

doi = "10.1109/ICCET.2009.128",

language = "English",

isbn = "9780769535210",

series = "Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009",

pages = "312--316",

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Thian, SO, Wee, HK & Andrew, BJT 2009, Dynamic handwritten signature verification based on statistical quantization mechanism. in Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009., 4769612, Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009, vol. 2, pp. 312-316. https://doi.org/10.1109/ICCET.2009.128

Dynamic handwritten signature verification based on statistical quantization mechanism. / Thian, Song Ong; Wee, How Khoh; Andrew, Beng Jin Teoh.
Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009. 2009. p. 312-316 4769612 (Proceedings - 2009 International Conference on Computer Engineering and Technology, ICCET 2009; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Online handwritten signature has been widely used for identity verification. However, it suffers from large intra-class variation problem as individual's signature may deviate from time to time due to variations in signing position, signature size, writing surface, and other factors. In addition, signatures are easier to forge than other biometrics and this leads to random and skilled forgeries issues. In this paper, we propose a novel Statistical Quantization Mechanism (SQM) to suppress the intra-class variation in signature features and thus discriminate the difference between genuine signature and its forgery. Experimental results show the proposed method is feasible in practice.

AB - Online handwritten signature has been widely used for identity verification. However, it suffers from large intra-class variation problem as individual's signature may deviate from time to time due to variations in signing position, signature size, writing surface, and other factors. In addition, signatures are easier to forge than other biometrics and this leads to random and skilled forgeries issues. In this paper, we propose a novel Statistical Quantization Mechanism (SQM) to suppress the intra-class variation in signature features and thus discriminate the difference between genuine signature and its forgery. Experimental results show the proposed method is feasible in practice.

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Dynamic handwritten signature verification based on statistical quantization mechanism

Abstract

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