Photometric Ligature Extraction Technique for Urdu Optical Character Recognition


  • M. Kazmi Faculty of Electrical and Computer Engineering, NED University of Engineering & Technology, Pakistan
  • F. Yasir Faculty of Electrical and Computer Engineering, NED University of Engineering & Technology, Pakistan
  • S. Habib Neurocomputation Lab, National Centre of Artificial Intelligence, NED University of Engineering and Technology, Pakistan
  • M. S. Hayat Deptartment of Electrical Engineering, NED University of Engineering and Technology, Pakistan
  • S. A. Qazi Neurocomputation Lab, National Centre of Artificial Intelligence, NED University of Engineering and Technology, Pakistan
Volume: 11 | Issue: 6 | Pages: 7968-7973 | December 2021 |


Urdu Optical Character Recognition (OCR) based on character level recognition (analytical approach) is less popular as compared to ligature level recognition (holistic approach) due to its added complexity, characters and strokes overlapping. This paper presents a holistic approach Urdu ligature extraction technique. The proposed Photometric Ligature Extraction (PLE) technique is independent of font size and column layout and is capable to handle non-overlapping and all inter and intra overlapping ligatures. It uses a customized photometric filter along with the application of X-shearing and padding with connected component analysis, to extract complete ligatures instead of extracting primary and secondary ligatures separately. A total of ~ 2,67,800 ligatures were extracted from scanned Urdu Nastaliq printed text images with an accuracy of 99.4%. Thus, the proposed framework outperforms the existing Urdu Nastaliq text extraction and segmentation algorithms. The proposed PLE framework can also be applied to other languages using the Nastaliq script style, languages such as Arabic, Persian, Pashto, and Sindhi.


ligature, holistic, Urdu OCR, Nastaliq, photometric filter, Urdu printed text images


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How to Cite

M. Kazmi, F. Yasir, S. Habib, M. S. Hayat, and S. A. Qazi, “Photometric Ligature Extraction Technique for Urdu Optical Character Recognition”, Eng. Technol. Appl. Sci. Res., vol. 11, no. 6, pp. 7968–7973, Dec. 2021.


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