An effective segmentation method for single stroke online cursive Arabic words

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 e...

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Bibliographic Details
Published in2010 International Conference on Computer Applications and Industrial Electronics pp. 217 - 221
Main Authors Potrus, M Y, Ngah, U K, Sakim, H A M
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2010
Subjects
Arabic Word Ligatures
Character recognition
Character Segmentation
Equations
Filtering
Handwriting recognition
Joints
Shape
Single Stroke
Writing
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Summary: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.
ISBN:1424490545
9781424490547
DOI:10.1109/ICCAIE.2010.5735078