Off-line signature verification and forgery detection system based on fuzzy modeling
This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. Th...
| Main Authors: | , , , |
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| Format: | Book Section |
| Language: | English |
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Springer Berlin Heidelberg
2003
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| Subjects: | |
| Online Access: | http://shdl.mmu.edu.my/2598/ http://shdl.mmu.edu.my/2598/1/Off-line%20signature%20verification%20and%20forgery%20detection%20system%20based%20on%20fuzzy%20modeling.pdf |
| _version_ | 1848790099007897600 |
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| author | Krishna Madasu, Vamsi Mohd. Hafizuddin Mohd. Yusof, K Hanmandlu, Madasu Kubik, Kurt |
| author_facet | Krishna Madasu, Vamsi Mohd. Hafizuddin Mohd. Yusof, K Hanmandlu, Madasu Kubik, Kurt |
| author_sort | Krishna Madasu, Vamsi |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (a) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system. |
| first_indexed | 2025-11-14T18:07:13Z |
| format | Book Section |
| id | mmu-2598 |
| institution | Multimedia University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:07:13Z |
| publishDate | 2003 |
| publisher | Springer Berlin Heidelberg |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-25982013-12-23T03:54:33Z http://shdl.mmu.edu.my/2598/ Off-line signature verification and forgery detection system based on fuzzy modeling Krishna Madasu, Vamsi Mohd. Hafizuddin Mohd. Yusof, K Hanmandlu, Madasu Kubik, Kurt QA75.5-76.95 Electronic computers. Computer science This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (a) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system. Springer Berlin Heidelberg 2003 Book Section NonPeerReviewed text en http://shdl.mmu.edu.my/2598/1/Off-line%20signature%20verification%20and%20forgery%20detection%20system%20based%20on%20fuzzy%20modeling.pdf Krishna Madasu, Vamsi and Mohd. Hafizuddin Mohd. Yusof, K and Hanmandlu, Madasu and Kubik, Kurt (2003) Off-line signature verification and forgery detection system based on fuzzy modeling. In: AI 2003: Advances in Artificial Intelligence. Lecture Notes in Computer Science, 2903 (2903). Springer Berlin Heidelberg, pp. 1003-1013. ISBN 978-3-540-20646-0 http://link.springer.com/chapter/10.1007%2F978-3-540-24581-0_86 10.1007/978-3-540-24581-0_86 10.1007/978-3-540-24581-0_86 10.1007/978-3-540-24581-0_86 |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Krishna Madasu, Vamsi Mohd. Hafizuddin Mohd. Yusof, K Hanmandlu, Madasu Kubik, Kurt Off-line signature verification and forgery detection system based on fuzzy modeling |
| title | Off-line signature verification and forgery detection system based on fuzzy modeling |
| title_full | Off-line signature verification and forgery detection system based on fuzzy modeling |
| title_fullStr | Off-line signature verification and forgery detection system based on fuzzy modeling |
| title_full_unstemmed | Off-line signature verification and forgery detection system based on fuzzy modeling |
| title_short | Off-line signature verification and forgery detection system based on fuzzy modeling |
| title_sort | off-line signature verification and forgery detection system based on fuzzy modeling |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2598/ http://shdl.mmu.edu.my/2598/ http://shdl.mmu.edu.my/2598/ http://shdl.mmu.edu.my/2598/1/Off-line%20signature%20verification%20and%20forgery%20detection%20system%20based%20on%20fuzzy%20modeling.pdf |