Hand Geometry Recognition System
This paper presents a useful biological approach for hand geometrybased recognition systems. Measurable hand geometry such as width, length, and finger area, were used to generate feature vectors. As useful properties, thirtyfive hand-shaped geometry scales are used. Artificial neural networks a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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College of Computer and Information Technology – University of Wasit, Iraq
2022-09-01
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| Series: | Wasit Journal of Computer and Mathematics Science |
| Online Access: | https://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/59 |
| _version_ | 1797198913899331584 |
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| author | Mays M. Taher Dr. Loay E. George |
| author_facet | Mays M. Taher Dr. Loay E. George |
| author_sort | Mays M. Taher |
| collection | DOAJ |
| description |
This paper presents a useful biological approach for hand geometrybased recognition systems. Measurable hand geometry such as width, length, and
finger area, were used to generate feature vectors. As useful properties, thirtyfive hand-shaped geometry scales are used. Artificial neural networks are used as
distinct classifiers. The experimental result of all dataset reaches to the
performance of 98.30% as recognition rate
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| first_indexed | 2024-03-07T19:03:13Z |
| format | Article |
| id | doaj.art-41acb280e5594b4a9c58450eb3ab117c |
| institution | Directory Open Access Journal |
| issn | 2788-5879 2788-5887 |
| language | English |
| last_indexed | 2024-04-24T07:07:25Z |
| publishDate | 2022-09-01 |
| publisher | College of Computer and Information Technology – University of Wasit, Iraq |
| record_format | Article |
| series | Wasit Journal of Computer and Mathematics Science |
| spelling | doaj.art-41acb280e5594b4a9c58450eb3ab117c2024-04-21T18:57:32ZengCollege of Computer and Information Technology – University of Wasit, IraqWasit Journal of Computer and Mathematics Science2788-58792788-58872022-09-011310.31185/wjcm.59Hand Geometry Recognition SystemMays M. Taher0Dr. Loay E. George1bachelor of computersUniversity of Information Technology And Communication This paper presents a useful biological approach for hand geometrybased recognition systems. Measurable hand geometry such as width, length, and finger area, were used to generate feature vectors. As useful properties, thirtyfive hand-shaped geometry scales are used. Artificial neural networks are used as distinct classifiers. The experimental result of all dataset reaches to the performance of 98.30% as recognition rate https://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/59 |
| spellingShingle | Mays M. Taher Dr. Loay E. George Hand Geometry Recognition System Wasit Journal of Computer and Mathematics Science |
| title | Hand Geometry Recognition System |
| title_full | Hand Geometry Recognition System |
| title_fullStr | Hand Geometry Recognition System |
| title_full_unstemmed | Hand Geometry Recognition System |
| title_short | Hand Geometry Recognition System |
| title_sort | hand geometry recognition system |
| url | https://wjcm.uowasit.edu.iq/index.php/wjcm/article/view/59 |
| work_keys_str_mv | AT maysmtaher handgeometryrecognitionsystem AT drloayegeorge handgeometryrecognitionsystem |