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ERIC Number: EJ1109572
Record Type: Journal
Publication Date: 2016-Sep
Pages: 17
Abstractor: As Provided
ISSN: ISSN-1360-2357
Segmentation Techniques for Recognition of Arabic-Like Scripts: A Comprehensive Survey
Naz, Saeeda; Umar, Arif I.; Shirazi, Syed H.; Ahmed, Saad B.; Razzak, Muhammad I.; Siddiqi, Imran
Education and Information Technologies, v21 n5 p1225-1241 Sep 2016
Arabic script-based text recognition system has been a popular field of research for many years that can be used in the learning and teaching process to the students and educators how to read and understand educational contents of Arabic script. The challenging nature of Arabic script recognition has attracted the attention of researchers from both industry and academic circles, but these efforts have not achieved good results until now. Segmentation of Urdu script when written in Nasta'liq writing style is a very difficult task due to the complexity of writing style as compared to Naskh writing style. Good segmentation is one of the reasons for high accuracy. Character segmentation has been a critical phase of the OCR process. The higher recognition rates for isolated characters as compared to results of words or connected character well illustrate the importance of segmentation. The current study investigates the recent work for character segmentation and challenges for segmentation for Arabic script-based languages.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A