Thinning of Balti Script : Way Forward to Balti OCR

Dil Nawaz Hakro; Abdul Majid; Muhammad Nadeem; Mashooq Ali Mahar; Qinbo; Dilawar Khan; Saba Brahmani

doi:10.32628/CSEIT2410428

Authors

Dil Nawaz Hakro Department of Software Engineering, FET, University of Sindh, Jamshoro, Pakistan Author
Abdul Majid Department of Computer Science and Technology, Faculty of Information Science and Engineering, Ocean University of China Author
Muhammad Nadeem Department of Computer Science and Technology, Faculty of Information Science and Engineering, Ocean University of China Author
Mashooq Ali Mahar Institute of Computer Science and Technology, Shah Abdul Latif University Khairpur Mirs Author
Qinbo Department of Computer Science and Technology, Faculty of Information Science and Engineering, Ocean University of China Author
Dilawar Khan Department of Computer Science and Technology, Faculty of Information Science and Engineering, Ocean University of China Author
Saba Brahmani Department of Computer Science and Technology, Faculty of Information Science and Engineering, Ocean University of China Author

DOI:

https://doi.org/10.32628/CSEIT2410428

Keywords:

Balti Language, Balti script, OCR, ICR, Thinning, Feature extraction

Abstract

Natural language is one of the applications of Artificial Intelligence, which trains machines to do the jobs in human language. OCR is one of the fields where the writing efforts are omitted and text images are converted into editable text. An OCR may have post and preprocessing to enhance the text image more suitable for the rest of the OCR process. Thinning is the preprocessing approach in which the characters, words and text is thinned to its one-pixel skeleton. Much of the work has been done in the various languages of the world as well as Pakistani languages. The work on Balti OCR is nonexistent. In this study, a thinning algorithm is proposed for the Balti language, a language spoken in the northern areas of Pakistan and India. Many of the Balti images were tested with the proposed algorithm and the proposed system produced accurate results by giving a one pixel skeleton of input image. The proposed algorithm tested with hundreds of Balti language images and selected results are presented in this paper. The current research has many directions including the way forward to building Balti OCR, Balti ICR (both segmentation based and segmentation free).

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