Finding critical points of handwritten Persian/Arabic character

On-line handwritten character recognition system is a special line of research in image processing and pattern recognition field, it can also considered a special process of in academic researches and production fields in the past decade. The general steps in a recognition system are pre-processing,...

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Main Authors: Harouni, Majid, Mohamad, Dzulkifli, Mohd. Rahim, Mohd. Shafry, M. Halawani, Sami
Format: Article
Published: International Association of Computer Science and Information Technology Press (IACSIT) 2012
Subjects:
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author Harouni, Majid
Mohamad, Dzulkifli
Mohd. Rahim, Mohd. Shafry
M. Halawani, Sami
author_facet Harouni, Majid
Mohamad, Dzulkifli
Mohd. Rahim, Mohd. Shafry
M. Halawani, Sami
author_sort Harouni, Majid
collection ePrints
description On-line handwritten character recognition system is a special line of research in image processing and pattern recognition field, it can also considered a special process of in academic researches and production fields in the past decade. The general steps in a recognition system are pre-processing, segmentation, feature extraction and classifications. The techniques of pre-processing stage play an excessive role in the system and directly affect the system performance. The focus of this article is on doing pre-processing stage and providing a most desirable data set form the raw data using in feature extraction and then to increase the rate of recognition system. For this reason, the novel algorithm is presented for finding a critical points set of hand-drawn letters. These critical points help extracting the correct structural and statistical features of on-line character handwriting in any given style writing.
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spelling utm.eprints-304762019-01-28T03:46:57Z http://eprints.utm.my/30476/ Finding critical points of handwritten Persian/Arabic character Harouni, Majid Mohamad, Dzulkifli Mohd. Rahim, Mohd. Shafry M. Halawani, Sami QA75 Electronic computers. Computer science On-line handwritten character recognition system is a special line of research in image processing and pattern recognition field, it can also considered a special process of in academic researches and production fields in the past decade. The general steps in a recognition system are pre-processing, segmentation, feature extraction and classifications. The techniques of pre-processing stage play an excessive role in the system and directly affect the system performance. The focus of this article is on doing pre-processing stage and providing a most desirable data set form the raw data using in feature extraction and then to increase the rate of recognition system. For this reason, the novel algorithm is presented for finding a critical points set of hand-drawn letters. These critical points help extracting the correct structural and statistical features of on-line character handwriting in any given style writing. International Association of Computer Science and Information Technology Press (IACSIT) 2012-10 Article PeerReviewed Harouni, Majid and Mohamad, Dzulkifli and Mohd. Rahim, Mohd. Shafry and M. Halawani, Sami (2012) Finding critical points of handwritten Persian/Arabic character. International Journal of Machine Learning and Computing, 2 (5). pp. 573-577. ISSN 2010-3700 http://dx.doi.org/10.7763/IJMLC.2012.V2.192 DOI: 10.7763/IJMLC.2012.V2.192
spellingShingle QA75 Electronic computers. Computer science
Harouni, Majid
Mohamad, Dzulkifli
Mohd. Rahim, Mohd. Shafry
M. Halawani, Sami
Finding critical points of handwritten Persian/Arabic character
title Finding critical points of handwritten Persian/Arabic character
title_full Finding critical points of handwritten Persian/Arabic character
title_fullStr Finding critical points of handwritten Persian/Arabic character
title_full_unstemmed Finding critical points of handwritten Persian/Arabic character
title_short Finding critical points of handwritten Persian/Arabic character
title_sort finding critical points of handwritten persian arabic character
topic QA75 Electronic computers. Computer science
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