DocumentCode
2777636
Title
An effective segmentation method for single stroke online cursive Arabic words
Author
Potrus, Moayad Yousif ; Ngah, Umi Kalthum ; Sakim, Harsa Amylia Mat
Author_Institution
Sch. of Electr. & Electron. Eng., Univ. Sains Malaysia, Nibong Tebal, Malaysia
fYear
2010
fDate
5-8 Dec. 2010
Firstpage
217
Lastpage
221
Abstract
A new method is used for character segmentation from cursive Arabic words. The method is based on statistical approach which uses Normalization and rectification, coordinate transformation and clustering to extract ligatures. The output is then filtered to extract start, overlapped and end segment errors. After applying the filter the characters are completely isolated and ready for recognition. The system, when testing the segmentation on 5 different Arabic sentences and by 20 different users, scored 98.03%, 94.82, 97.33 and 90% for normal segment, starting segment, last segment and overlapped segment.
Keywords
feature extraction; handwritten character recognition; image segmentation; natural language processing; pattern clustering; character segmentation; clustering; coordinate transformation; ligatures extraction; normalization; rectification; single stroke online cursive Arabic words; Character recognition; Equations; Filtering; Handwriting recognition; Joints; Shape; Writing; Arabic Word Ligatures; Character Segmentation; Single Stroke;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4244-9054-7
Type
conf
DOI
10.1109/ICCAIE.2010.5735078
Filename
5735078
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