Glyph Identification and Character Recognition for Sindhi OCR

  • Nisar Ahmed Memon Department of Computer Engineering, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia.
  • Fatima Abbasi Department of Information Technology, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah.
  • Shehnila Zardari Department of Computer Science and Software Engineering, NED University of Engineering Techology, Karachi.


A computer can read and write multiple languages and today’s computers are capable of understanding various human languages. A computer can be given instructions through various input methods but OCR (Optical Character Recognition) and handwritten character recognition are the input methods in which a scanned page containing text is converted into written or editable text. The change in language
text available on scanned page demands different algorithm to recognize text because every language and script pose varying number of challenges to recognize text. The Latin language recognition pose less difficulties compared to Arabic script and languages that use Arabic script for writing and OCR systems for these Latin languages are near to perfection. Very little work has been done on regional languages of Pakistan. In this paper the Sindhi glyphs are identified and the number of characters and connected components are identified for this regional language of Pakistan. A graphical user interface has been created to perform identification task for glyphs and characters of Sindhi language. The glyphs of characters are successfully identified from scanned page and this information can be used to recognize
characters. The language glyph identification can be used to apply suitable algorithm to identify language as well as to achieve a higher recognition rate.

Oct 1, 2017
How to Cite
MEMON, Nisar Ahmed; ABBASI, Fatima; ZARDARI, Shehnila. Glyph Identification and Character Recognition for Sindhi OCR. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 36, n. 4, p. 8, oct. 2017. ISSN 2413-7219. Available at: <>. Date accessed: 28 feb. 2020. doi:
This is an open Access Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License