Verifying on-line handwritten signature using neural networks approach
Signatures are used everyday to authorize the transfer of funds for bank cheques, credit cards, legal documents and others. Forgeries on banking and business transactions amount to a large sum of money every year. Although the cashier sometimes can spot the forgeries, it is not cost effective to che...
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| Format: | Book Section |
| Language: | English |
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Pusat Penyelidikan dan Perundingan, Universiti Utara Malaysia
2000
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/2284/1/FADZILLAH_SIRAJ_%282001%29_01.pdf |
| _version_ | 1803624451428843520 |
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| author | Siraj, Fadzilah Zakaria, Azizi Wan Ishak, Wan Hussain |
| author2 | Mohamed Hanefah, Hajah Mustafa |
| author_facet | Mohamed Hanefah, Hajah Mustafa Siraj, Fadzilah Zakaria, Azizi Wan Ishak, Wan Hussain |
| author_sort | Siraj, Fadzilah |
| collection | UUM |
| description | Signatures are used everyday to authorize the transfer of funds for bank cheques, credit cards, legal documents and others. Forgeries on banking and business transactions amount to a large sum of money every year. Although the cashier sometimes can spot the forgeries, it is not cost effective to check the forgeries manually. Hence, automated verification is available, this will certainly benefit the
customers and promote Electronic Commerce. Thus handwritten signature verification system can play an important role in future reading system (Bartneck, 1996).It is a worthy and challenging area of further investigation (Cote et, al, 1998). This paper discusses the neural network models and thus identifies suitable model for on-line Handwritten Signature Verification. Such a model is implemented and the
performance of the neural network model is evaluated. |
| first_indexed | 2024-07-04T05:18:35Z |
| format | Book Section |
| id | uum-2284 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T05:18:35Z |
| publishDate | 2000 |
| publisher | Pusat Penyelidikan dan Perundingan, Universiti Utara Malaysia |
| record_format | dspace |
| spelling | uum-22842011-02-21T05:55:20Z https://repo.uum.edu.my/id/eprint/2284/ Verifying on-line handwritten signature using neural networks approach Siraj, Fadzilah Zakaria, Azizi Wan Ishak, Wan Hussain QA75 Electronic computers. Computer science Signatures are used everyday to authorize the transfer of funds for bank cheques, credit cards, legal documents and others. Forgeries on banking and business transactions amount to a large sum of money every year. Although the cashier sometimes can spot the forgeries, it is not cost effective to check the forgeries manually. Hence, automated verification is available, this will certainly benefit the customers and promote Electronic Commerce. Thus handwritten signature verification system can play an important role in future reading system (Bartneck, 1996).It is a worthy and challenging area of further investigation (Cote et, al, 1998). This paper discusses the neural network models and thus identifies suitable model for on-line Handwritten Signature Verification. Such a model is implemented and the performance of the neural network model is evaluated. Pusat Penyelidikan dan Perundingan, Universiti Utara Malaysia Mohamed Hanefah, Hajah Mustafa 2000 Book Section PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/2284/1/FADZILLAH_SIRAJ_%282001%29_01.pdf Siraj, Fadzilah and Zakaria, Azizi and Wan Ishak, Wan Hussain (2000) Verifying on-line handwritten signature using neural networks approach. In: Prosiding Seminar Penyelidikan UUM 2000. Pusat Penyelidikan dan Perundingan, Universiti Utara Malaysia, Sintok, pp. 298-315. ISBN 9832479010 http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000200706 |
| spellingShingle | QA75 Electronic computers. Computer science Siraj, Fadzilah Zakaria, Azizi Wan Ishak, Wan Hussain Verifying on-line handwritten signature using neural networks approach |
| title | Verifying on-line handwritten signature using neural networks approach |
| title_full | Verifying on-line handwritten signature using neural networks approach |
| title_fullStr | Verifying on-line handwritten signature using neural networks approach |
| title_full_unstemmed | Verifying on-line handwritten signature using neural networks approach |
| title_short | Verifying on-line handwritten signature using neural networks approach |
| title_sort | verifying on line handwritten signature using neural networks approach |
| topic | QA75 Electronic computers. Computer science |
| url | https://repo.uum.edu.my/id/eprint/2284/1/FADZILLAH_SIRAJ_%282001%29_01.pdf |
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