Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India

Research Article

Handwritten Myanmar Character Recognition System using the Otsu’s Binarization Algorithm

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  • @INPROCEEDINGS{10.4108/eai.27-2-2020.2303219,
        author={Aye Aye Nyein and Hlaing Htake Khaung Tin},
        title={Handwritten Myanmar Character Recognition System using the Otsu’s Binarization Algorithm},
        proceedings={Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India},
        publisher={EAI},
        proceedings_a={ICIDSSD},
        year={2021},
        month={3},
        keywords={handwritten myanar character recognition system feature extraction edge detection},
        doi={10.4108/eai.27-2-2020.2303219}
    }
    
  • Aye Aye Nyein
    Hlaing Htake Khaung Tin
    Year: 2021
    Handwritten Myanmar Character Recognition System using the Otsu’s Binarization Algorithm
    ICIDSSD
    EAI
    DOI: 10.4108/eai.27-2-2020.2303219
Aye Aye Nyein1,*, Hlaing Htake Khaung Tin2
  • 1: Faculty of Computer Science, University of Computer Studies, Hinthada, Myanmar
  • 2: Faculty of Infomation Science, University of Computer Studies, Hinthada, Myanmar
*Contact email: ayeayenyein2008@gmail.com

Abstract

Handwritten is a famous techniques involved in many recognition system in image processing and pattern recognition. In this paper, first step is pre-processing includes noise reduction, colour conversion and edge detection method to segment Handwritten Myanmar Characters from the image. Also, Open Source Tesseract OCR engine is used to recognize the segmented Handwritten Myanmar Characters. The recognition accuracy will highly depend on the good segmentation. Some of the handwritten recognition applications are criminal documentation, security method, image and Movie managing and medical science research on Myanmar character recognition is still in its early days with limited literature available till date