Writer identification based on hyper sausage neuron
This paper proposes biomimetic pattern recognition (BPR) based on hyper sausage neuron (HSN) and applies it in writer identification. HSN is used to cover the training set.HSN’s coverage can be seen as a topological product of a one-dimensional line segment and an n-dimensional supersphere.The feat...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/13605/1/49.pdf |
| _version_ | 1825803216539877376 |
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| author | Samsuryadi, , Shamsuddin, Siti Mariyam Ahmad, Norbahiah |
| author_facet | Samsuryadi, , Shamsuddin, Siti Mariyam Ahmad, Norbahiah |
| author_sort | Samsuryadi, , |
| collection | UUM |
| description | This paper proposes biomimetic pattern recognition (BPR) based on hyper sausage neuron (HSN) and applies it in writer identification. HSN is used to cover the training set.HSN’s coverage can be seen as a
topological product of a one-dimensional line segment and an n-dimensional supersphere.The feature extraction is moment invariants such as united moment invariants (UMI) and aspect united moment invariants (AUMI).The experiments result show that AUMI-HSN method is more effective than UMI-HSN method for identifying the authorship of handwriting. |
| first_indexed | 2024-07-04T05:53:13Z |
| format | Conference or Workshop Item |
| id | uum-13605 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T05:53:13Z |
| publishDate | 2011 |
| record_format | eprints |
| spelling | uum-136052015-04-07T04:37:04Z https://repo.uum.edu.my/id/eprint/13605/ Writer identification based on hyper sausage neuron Samsuryadi, , Shamsuddin, Siti Mariyam Ahmad, Norbahiah QA76 Computer software This paper proposes biomimetic pattern recognition (BPR) based on hyper sausage neuron (HSN) and applies it in writer identification. HSN is used to cover the training set.HSN’s coverage can be seen as a topological product of a one-dimensional line segment and an n-dimensional supersphere.The feature extraction is moment invariants such as united moment invariants (UMI) and aspect united moment invariants (AUMI).The experiments result show that AUMI-HSN method is more effective than UMI-HSN method for identifying the authorship of handwriting. 2011-06-08 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/13605/1/49.pdf Samsuryadi, , and Shamsuddin, Siti Mariyam and Ahmad, Norbahiah (2011) Writer identification based on hyper sausage neuron. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011, Bandung, Indonesia. http://www.icoci.cms.net.my |
| spellingShingle | QA76 Computer software Samsuryadi, , Shamsuddin, Siti Mariyam Ahmad, Norbahiah Writer identification based on hyper sausage neuron |
| title | Writer identification based on hyper sausage neuron |
| title_full | Writer identification based on hyper sausage neuron |
| title_fullStr | Writer identification based on hyper sausage neuron |
| title_full_unstemmed | Writer identification based on hyper sausage neuron |
| title_short | Writer identification based on hyper sausage neuron |
| title_sort | writer identification based on hyper sausage neuron |
| topic | QA76 Computer software |
| url | https://repo.uum.edu.my/id/eprint/13605/1/49.pdf |
| work_keys_str_mv | AT samsuryadi writeridentificationbasedonhypersausageneuron AT shamsuddinsitimariyam writeridentificationbasedonhypersausageneuron AT ahmadnorbahiah writeridentificationbasedonhypersausageneuron |