Intelligent biometric signature verification system incorporating neural network
In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing sta...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering
2005
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| Online Access: | http://eprints.utm.my/6492/1/LimBoonHan2005_Intelligent_biometric_signature_verification_system.pdf |
| _version_ | 1796854083466821632 |
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| author | Lim, Boon Han Mailah, Musa |
| author_facet | Lim, Boon Han Mailah, Musa |
| author_sort | Lim, Boon Han |
| collection | ePrints |
| description | In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing stage of the acquired signature signals involving the use of a number of common feature extraction techniques is rigorously highlighted. An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. The results of the study showed that the system is effective and promising in identifying correct human signatures presented to the system. |
| first_indexed | 2024-03-05T18:09:06Z |
| format | Article |
| id | utm.eprints-6492 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:09:06Z |
| publishDate | 2005 |
| publisher | Faculty of Mechanical Engineering |
| record_format | dspace |
| spelling | utm.eprints-64922010-06-01T15:43:44Z http://eprints.utm.my/6492/ Intelligent biometric signature verification system incorporating neural network Lim, Boon Han Mailah, Musa TJ Mechanical engineering and machinery In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing stage of the acquired signature signals involving the use of a number of common feature extraction techniques is rigorously highlighted. An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. The results of the study showed that the system is effective and promising in identifying correct human signatures presented to the system. Faculty of Mechanical Engineering 2005 Article PeerReviewed application/pdf en http://eprints.utm.my/6492/1/LimBoonHan2005_Intelligent_biometric_signature_verification_system.pdf Lim, Boon Han and Mailah, Musa (2005) Intelligent biometric signature verification system incorporating neural network. Jurnal Mekanikal (20). pp. 22-41. ISSN 0127-3396 https://www.fkm.utm.my/~mekanika |
| spellingShingle | TJ Mechanical engineering and machinery Lim, Boon Han Mailah, Musa Intelligent biometric signature verification system incorporating neural network |
| title | Intelligent biometric signature verification system incorporating neural network |
| title_full | Intelligent biometric signature verification system incorporating neural network |
| title_fullStr | Intelligent biometric signature verification system incorporating neural network |
| title_full_unstemmed | Intelligent biometric signature verification system incorporating neural network |
| title_short | Intelligent biometric signature verification system incorporating neural network |
| title_sort | intelligent biometric signature verification system incorporating neural network |
| topic | TJ Mechanical engineering and machinery |
| url | http://eprints.utm.my/6492/1/LimBoonHan2005_Intelligent_biometric_signature_verification_system.pdf |
| work_keys_str_mv | AT limboonhan intelligentbiometricsignatureverificationsystemincorporatingneuralnetwork AT mailahmusa intelligentbiometricsignatureverificationsystemincorporatingneuralnetwork |