Automatic online signature verification: A prototype using neural networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Signature verification is the process used to recognize an individual's handwritten signature to prevent fraud. In this paper pressure at the pen-tip together with the x, and y coordinates of the signature are measured and features extracted from these are used to verify the signature. A pressure pad was used to obtain signature samples. A signature verification system using SOM neural network was designed in MATLAB to verify the signatures. Results obtained using a prototype system are encouraging. The attractive features of this system are its low cost, low intrusion, good performance and use of an acceptable and natural biometric (the signature).

Original languageEnglish
Title of host publicationTENCON 2009 - 2009 IEEE Region 10 Conference
DOIs
Publication statusPublished - 01 Dec 2009
Event2009 IEEE Region 10 Conference, TENCON 2009 - Singapore, Singapore
Duration: 23 Nov 200926 Nov 2009

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON

Other

Other2009 IEEE Region 10 Conference, TENCON 2009
CountrySingapore
CitySingapore
Period23/11/0926/11/09

Fingerprint

Neural networks
Biometrics
MATLAB
Costs

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Khaleel Ahmed, S., Ramasamy, A., Khairuddin, A. S. M., & Omar, J. (2009). Automatic online signature verification: A prototype using neural networks. In TENCON 2009 - 2009 IEEE Region 10 Conference [5395951] (IEEE Region 10 Annual International Conference, Proceedings/TENCON). https://doi.org/10.1109/TENCON.2009.5395951
Khaleel Ahmed, Syed ; Ramasamy, Agileswari ; Khairuddin, Anis Salwa Mohd ; Omar, Jamaludin. / Automatic online signature verification : A prototype using neural networks. TENCON 2009 - 2009 IEEE Region 10 Conference. 2009. (IEEE Region 10 Annual International Conference, Proceedings/TENCON).
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abstract = "Signature verification is the process used to recognize an individual's handwritten signature to prevent fraud. In this paper pressure at the pen-tip together with the x, and y coordinates of the signature are measured and features extracted from these are used to verify the signature. A pressure pad was used to obtain signature samples. A signature verification system using SOM neural network was designed in MATLAB to verify the signatures. Results obtained using a prototype system are encouraging. The attractive features of this system are its low cost, low intrusion, good performance and use of an acceptable and natural biometric (the signature).",
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Khaleel Ahmed, S, Ramasamy, A, Khairuddin, ASM & Omar, J 2009, Automatic online signature verification: A prototype using neural networks. in TENCON 2009 - 2009 IEEE Region 10 Conference., 5395951, IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2009 IEEE Region 10 Conference, TENCON 2009, Singapore, Singapore, 23/11/09. https://doi.org/10.1109/TENCON.2009.5395951

Automatic online signature verification : A prototype using neural networks. / Khaleel Ahmed, Syed; Ramasamy, Agileswari; Khairuddin, Anis Salwa Mohd; Omar, Jamaludin.

TENCON 2009 - 2009 IEEE Region 10 Conference. 2009. 5395951 (IEEE Region 10 Annual International Conference, Proceedings/TENCON).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Signature verification is the process used to recognize an individual's handwritten signature to prevent fraud. In this paper pressure at the pen-tip together with the x, and y coordinates of the signature are measured and features extracted from these are used to verify the signature. A pressure pad was used to obtain signature samples. A signature verification system using SOM neural network was designed in MATLAB to verify the signatures. Results obtained using a prototype system are encouraging. The attractive features of this system are its low cost, low intrusion, good performance and use of an acceptable and natural biometric (the signature).

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Khaleel Ahmed S, Ramasamy A, Khairuddin ASM, Omar J. Automatic online signature verification: A prototype using neural networks. In TENCON 2009 - 2009 IEEE Region 10 Conference. 2009. 5395951. (IEEE Region 10 Annual International Conference, Proceedings/TENCON). https://doi.org/10.1109/TENCON.2009.5395951