An adaptive approach for Malay cheque words recognition using support vector machine
Support vector machines (SVMs) have played a significant role in the field of pattern recognition. This study utilizes the SVM as a classifier for the analysis of Malay cheque word recognition using Malay lexical database (Ahmad et al., 2007). The SVM system was used for individual character recogni...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Academic Journals
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/23119/ http://psasir.upm.edu.my/id/eprint/23119/1/An%20adaptive%20approach%20for%20Malay%20cheque%20words.pdf |
| _version_ | 1848844668735848448 |
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| author | Al Boredi, Omar Noori Salih Syed Ahmad Abdul Rahman, Sharifah Mumtazah Shakil, Asma |
| author_facet | Al Boredi, Omar Noori Salih Syed Ahmad Abdul Rahman, Sharifah Mumtazah Shakil, Asma |
| author_sort | Al Boredi, Omar Noori Salih |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Support vector machines (SVMs) have played a significant role in the field of pattern recognition. This study utilizes the SVM as a classifier for the analysis of Malay cheque word recognition using Malay lexical database (Ahmad et al., 2007). The SVM system was used for individual character recognition and then lexical verification was applied for word level. Several pre-processing steps were taken such as noise removal, image normalization, and skeletonization prior to feature extraction to improve the dataset perspective and hence the recognition accuracy. Statistical and geometrical extraction techniques have been applied in the approach. The results show that the statistical feature is reliable, accessible and provides more accurate results. The results also show that the new approach passed 97.15% character recognition, and combined with word lexical verification, the recognition rate surpassed 98.2% recognition rate. |
| first_indexed | 2025-11-15T08:34:35Z |
| format | Article |
| id | upm-23119 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:34:35Z |
| publishDate | 2011 |
| publisher | Academic Journals |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-231192018-10-18T07:04:43Z http://psasir.upm.edu.my/id/eprint/23119/ An adaptive approach for Malay cheque words recognition using support vector machine Al Boredi, Omar Noori Salih Syed Ahmad Abdul Rahman, Sharifah Mumtazah Shakil, Asma Support vector machines (SVMs) have played a significant role in the field of pattern recognition. This study utilizes the SVM as a classifier for the analysis of Malay cheque word recognition using Malay lexical database (Ahmad et al., 2007). The SVM system was used for individual character recognition and then lexical verification was applied for word level. Several pre-processing steps were taken such as noise removal, image normalization, and skeletonization prior to feature extraction to improve the dataset perspective and hence the recognition accuracy. Statistical and geometrical extraction techniques have been applied in the approach. The results show that the statistical feature is reliable, accessible and provides more accurate results. The results also show that the new approach passed 97.15% character recognition, and combined with word lexical verification, the recognition rate surpassed 98.2% recognition rate. Academic Journals 2011-03 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/23119/1/An%20adaptive%20approach%20for%20Malay%20cheque%20words.pdf Al Boredi, Omar Noori Salih and Syed Ahmad Abdul Rahman, Sharifah Mumtazah and Shakil, Asma (2011) An adaptive approach for Malay cheque words recognition using support vector machine. Scientific Research and Essays, 6 (6). art. no. 6D71C7023325. pp. 1328-1336. ISSN 1992-2248 https://academicjournals.org/journal/SRE/article-abstract/6D71C7023325 10.5897/SRE10.1021 |
| spellingShingle | Al Boredi, Omar Noori Salih Syed Ahmad Abdul Rahman, Sharifah Mumtazah Shakil, Asma An adaptive approach for Malay cheque words recognition using support vector machine |
| title | An adaptive approach for Malay cheque words recognition using support vector machine |
| title_full | An adaptive approach for Malay cheque words recognition using support vector machine |
| title_fullStr | An adaptive approach for Malay cheque words recognition using support vector machine |
| title_full_unstemmed | An adaptive approach for Malay cheque words recognition using support vector machine |
| title_short | An adaptive approach for Malay cheque words recognition using support vector machine |
| title_sort | adaptive approach for malay cheque words recognition using support vector machine |
| url | http://psasir.upm.edu.my/id/eprint/23119/ http://psasir.upm.edu.my/id/eprint/23119/ http://psasir.upm.edu.my/id/eprint/23119/ http://psasir.upm.edu.my/id/eprint/23119/1/An%20adaptive%20approach%20for%20Malay%20cheque%20words.pdf |