Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/2374
Title: Printed Arabic optical character segmentation
Authors: Mohammad, Khader 
Ayyesh, Muna 
Qaroush, Aziz 
Tumar, Iyad 
Keywords: Optical Character Recognition;Arabic character sets (Data processing);Arabic language - Phonetic transcriptions;Arabic language - Data processing
Issue Date: 2015
Publisher: ACM
Conference: Image Processing : Algorithms and Systems (13th : 2015 : San Francisco, Calif., US) 
Abstract: A considerable progress in recognition techniques for many non-Arabic characters has been achieved. In contrary, few efforts have been put on the research of Arabic characters. In any Optical Character Recognition (OCR) system the segmentation step is usually the essential stage in which an extensive portion of processing is devoted and a considerable share of recognition errors is attributed. In this research, a novel segmentation approach for machine Arabic printed text with diacritics is proposed. The proposed method reduces computation, errors, gives a clear description for the sub-word and has advantages over using the skeleton approach in which the data and information of the character can be lost. Both of initial evaluation and testing of the proposed method have been developed using MATLAB and shows 98.7% promising results
Description: A paper submitted to conference : Image Processing : Algorithms and Systems XIII, 10–11 February 2015, San Francisco, California, United States
URI: http://hdl.handle.net/20.500.11889/2374
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