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 language | English |
|---|---|
| Title of host publication | TENCON 2009 - 2009 IEEE Region 10 Conference |
| DOIs | |
| Publication status | Published - 01 Dec 2009 |
| Event | 2009 IEEE Region 10 Conference, TENCON 2009 - Singapore, Singapore Duration: 23 Nov 2009 → 26 Nov 2009 |
Publication series
| Name | IEEE Region 10 Annual International Conference, Proceedings/TENCON |
|---|
Other
| Other | 2009 IEEE Region 10 Conference, TENCON 2009 |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 23/11/09 → 26/11/09 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
Cite this
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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 proceeding › Conference contribution
TY - GEN
T1 - Automatic online signature verification
T2 - A prototype using neural networks
AU - Khaleel Ahmed, Syed
AU - Ramasamy, Agileswari
AU - Khairuddin, Anis Salwa Mohd
AU - Omar, Jamaludin
PY - 2009/12/1
Y1 - 2009/12/1
N2 - 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).
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).
UR - http://www.scopus.com/inward/record.url?scp=77951133463&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951133463&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2009.5395951
DO - 10.1109/TENCON.2009.5395951
M3 - Conference contribution
AN - SCOPUS:77951133463
SN - 9781424445479
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
BT - TENCON 2009 - 2009 IEEE Region 10 Conference
ER -