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
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;
Conference_Titel :
Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-9054-7
DOI :
10.1109/ICCAIE.2010.5735078