Fuzzy C mean clustering in off-line handwriting signature verfication system
This research is the first research that suggests the usage of the stable region of a signature for verification purpose. This research highlighted the design and development of the proposed Fuzzy C Mean clustering to determine the stable segments of a signature generated from windowing segmentation...
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Faculty of Computer Science and Information Technology
2006
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| Online Access: | http://ir.unimas.my/id/eprint/1705/8/2013-02-thLeeBYfull.pdf http://ir.unimas.my/id/eprint/1705/ |
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| Institution: | Universiti Malaysia Sarawak |
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my.unimas.ir.17052023-03-07T08:20:04Z http://ir.unimas.my/id/eprint/1705/ Fuzzy C mean clustering in off-line handwriting signature verfication system Lee, Beng Yong QA76 Computer software This research is the first research that suggests the usage of the stable region of a signature for verification purpose. This research highlighted the design and development of the proposed Fuzzy C Mean clustering to determine the stable segments of a signature generated from windowing segmentation process where features could be extracted from signature images. Six features are extracted from each stable segment i.e. Image Size, Ratio of height to width, slant, Maximum horizontal projection, Vertical centre of mass and Horizontal Relative gravity centre/ Horizontal centre of mass. Besides that, this research also demonstrated how to select a best features to represent each determined stable segment. Faculty of Computer Science and Information Technology 2006 Thesis NonPeerReviewed text en http://ir.unimas.my/id/eprint/1705/8/2013-02-thLeeBYfull.pdf Lee, Beng Yong (2006) Fuzzy C mean clustering in off-line handwriting signature verfication system. Masters thesis, Universiti Malaysia Sarawak (UNIMAS). |
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QA76 Computer software |
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QA76 Computer software Lee, Beng Yong Fuzzy C mean clustering in off-line handwriting signature verfication system |
| description |
This research is the first research that suggests the usage of the stable region of a signature for verification purpose. This research highlighted the design and development of the proposed Fuzzy C Mean clustering to determine the stable segments of a signature generated from windowing segmentation process where features could be extracted from signature images. Six features are extracted from each stable segment i.e. Image Size, Ratio of height to width, slant, Maximum horizontal projection, Vertical centre of mass and Horizontal Relative gravity centre/ Horizontal centre of mass. Besides that, this research also demonstrated how to select a best features to represent each determined stable segment. |
| format |
Thesis |
| author |
Lee, Beng Yong |
| author_facet |
Lee, Beng Yong |
| author_sort |
Lee, Beng Yong |
| title |
Fuzzy C mean clustering in off-line handwriting signature verfication system |
| title_short |
Fuzzy C mean clustering in off-line handwriting signature verfication system |
| title_full |
Fuzzy C mean clustering in off-line handwriting signature verfication system |
| title_fullStr |
Fuzzy C mean clustering in off-line handwriting signature verfication system |
| title_full_unstemmed |
Fuzzy C mean clustering in off-line handwriting signature verfication system |
| title_sort |
fuzzy c mean clustering in off-line handwriting signature verfication system |
| publisher |
Faculty of Computer Science and Information Technology |
| publishDate |
2006 |
| url |
http://ir.unimas.my/id/eprint/1705/8/2013-02-thLeeBYfull.pdf http://ir.unimas.my/id/eprint/1705/ |
| _version_ |
1761623518167957504 |