Feature extraction techniques of online handwriting arabic text recognition
Online recognition of Arabic handwritten text has been an ongoing research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. Most of the onlin...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/30997/ http://irep.iium.edu.my/30997/1/Table_of_Content.pdf http://irep.iium.edu.my/30997/2/Feature_Extraction_Techniques_of_Online_Handwriting_Arabic_Text_Recognition1.pdf |
| _version_ | 1848780367951036416 |
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| author | Abuzaraida, Mustafa Ali Zeki, Akram M. Zeki, Ahmed M. |
| author_facet | Abuzaraida, Mustafa Ali Zeki, Akram M. Zeki, Ahmed M. |
| author_sort | Abuzaraida, Mustafa Ali |
| building | IIUM Repository |
| collection | Online Access |
| description | Online recognition of Arabic handwritten text has been an ongoing research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. Most of the online text recognition systems consist of three main phases which are preprocessing, feature extraction, and recognition phase. This paper compares between different techniques that have been used to extract the features of Arabic handwriting scripts in online recognition systems. Those techniques attempt to extract the feature vector of Arabic handwritten words, characters, numbers or strokes. This vector then will be fed into the recognition engine to recognize the pattern using the feature vector. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed. |
| first_indexed | 2025-11-14T15:32:33Z |
| format | Proceeding Paper |
| id | iium-30997 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T15:32:33Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-309972014-12-08T03:46:08Z http://irep.iium.edu.my/30997/ Feature extraction techniques of online handwriting arabic text recognition Abuzaraida, Mustafa Ali Zeki, Akram M. Zeki, Ahmed M. QA75 Electronic computers. Computer science QA76 Computer software T58.5 Information technology Online recognition of Arabic handwritten text has been an ongoing research problem for many years. Generally, online text recognition field has been gaining more interest lately due to the increasing popularity of hand-held computers, digital notebooks and advanced cellular phones. Most of the online text recognition systems consist of three main phases which are preprocessing, feature extraction, and recognition phase. This paper compares between different techniques that have been used to extract the features of Arabic handwriting scripts in online recognition systems. Those techniques attempt to extract the feature vector of Arabic handwritten words, characters, numbers or strokes. This vector then will be fed into the recognition engine to recognize the pattern using the feature vector. The structure and strategy of those reviewed techniques are explained in this article. The strengths and weaknesses of using these techniques will also be discussed. 2013 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/30997/1/Table_of_Content.pdf application/pdf en http://irep.iium.edu.my/30997/2/Feature_Extraction_Techniques_of_Online_Handwriting_Arabic_Text_Recognition1.pdf Abuzaraida, Mustafa Ali and Zeki, Akram M. and Zeki, Ahmed M. (2013) Feature extraction techniques of online handwriting arabic text recognition. In: The 4th International Conference on Information & Communication Technology for the Muslim World (ICT4M), 25-27 Mar 2013, Rabat, Moroco. http://ict4m.org/ |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software T58.5 Information technology Abuzaraida, Mustafa Ali Zeki, Akram M. Zeki, Ahmed M. Feature extraction techniques of online handwriting arabic text recognition |
| title | Feature extraction techniques of online handwriting arabic text recognition |
| title_full | Feature extraction techniques of online handwriting arabic text recognition |
| title_fullStr | Feature extraction techniques of online handwriting arabic text recognition |
| title_full_unstemmed | Feature extraction techniques of online handwriting arabic text recognition |
| title_short | Feature extraction techniques of online handwriting arabic text recognition |
| title_sort | feature extraction techniques of online handwriting arabic text recognition |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T58.5 Information technology |
| url | http://irep.iium.edu.my/30997/ http://irep.iium.edu.my/30997/ http://irep.iium.edu.my/30997/1/Table_of_Content.pdf http://irep.iium.edu.my/30997/2/Feature_Extraction_Techniques_of_Online_Handwriting_Arabic_Text_Recognition1.pdf |