Verifying online signatures through an iterative device independent model
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.
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| Materyal Türü: | Tez |
| Dil: | English |
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Brac University
2024
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| Online Erişim: | http://hdl.handle.net/10361/22849 |
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10361-228492024-05-16T21:01:00Z Verifying online signatures through an iterative device independent model Tahsin, Samiha Molla, Robin Jamal, Omran Islam, Md Saiful Rahman, Rafeed Department of Computer Science and Engineering, Brac University Signature verification e-Signature Machine learning Pattern perception--Data processing Pattern perception Deep learning (Machine learning) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 20-21). Hand signatures are getting used from as early as we invented writing. In 3100 BC, we found examples of people using words and symbols to denote their identity. It has also been used as a method of identification. Modern society kept hand signatures for many purposes like the authentication of banking and real estate fields. The recent trend of working from home and business on the go created a necessity to bring the signature from paper to smartphone. Statistics also indicated that it is a user-preferred method of verification. In this paper, we proposed a novel method to verify online signatures using an iterative approach that is device independent. It will be helpful to bring the signatures from paper to smartphones. In this method, we have created a model per signatory, based on their behavioral pattern on each point based on time and distance from the start of the signature. We also considered the defference between the signatory’s own signatures while training. We worked with defferent derived datapoints like velocity, angular velocity etc. We have achieved 8% EER on the MCYT dataset and 20% EER on the Mobisig dataset. Samiha Tahsin Robin Molla Omran Jamal B.Sc in Computer Science 2024-05-16T05:48:34Z 2024-05-16T05:48:34Z ©2023 2023-01 Thesis ID: 18101265 ID: 21241081 ID: 18101263 http://hdl.handle.net/10361/22849 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 34 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Signature verification e-Signature Machine learning Pattern perception--Data processing Pattern perception Deep learning (Machine learning) |
| spellingShingle |
Signature verification e-Signature Machine learning Pattern perception--Data processing Pattern perception Deep learning (Machine learning) Tahsin, Samiha Molla, Robin Jamal, Omran Verifying online signatures through an iterative device independent model |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. |
| author2 |
Islam, Md Saiful |
| author_facet |
Islam, Md Saiful Tahsin, Samiha Molla, Robin Jamal, Omran |
| format |
Thesis |
| author |
Tahsin, Samiha Molla, Robin Jamal, Omran |
| author_sort |
Tahsin, Samiha |
| title |
Verifying online signatures through an iterative device independent model |
| title_short |
Verifying online signatures through an iterative device independent model |
| title_full |
Verifying online signatures through an iterative device independent model |
| title_fullStr |
Verifying online signatures through an iterative device independent model |
| title_full_unstemmed |
Verifying online signatures through an iterative device independent model |
| title_sort |
verifying online signatures through an iterative device independent model |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/22849 |
| work_keys_str_mv |
AT tahsinsamiha verifyingonlinesignaturesthroughaniterativedeviceindependentmodel AT mollarobin verifyingonlinesignaturesthroughaniterativedeviceindependentmodel AT jamalomran verifyingonlinesignaturesthroughaniterativedeviceindependentmodel |
| _version_ |
1814307441298374656 |