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Text Translation of Scanned Hindi Document to Braille via Image Processing


  • School of Electronics Engineering, KIIT University, Bhubaneswar – 751024, Odisha, India


Objective: Braille - a model to reduce the illiteracy rate among the visually challenged people. So, this paper focuses on text translation/ conversion of scanned Hindi document to Braille, a single mode of communication for visually challenged people via Image processing techniques. Method/Analysis: The translation of scanned Hindi text into Braille code involves the following four processes: (i) Hindi database generation of consonants and matras using image segmentation. (ii) Segmentation of test images into lines followed by words and finally into letters. This step involves three types of segmentation: (a) line segmentation (b) word segmentation (c) letter segmentation. (iii) Letter matching of segmented letters with the generated Hindi database using Principal Component Analysis (PCA). (iv) Conversion of matched letter into corresponding Braille code. The algorithm takes test documents as input and reads the letter wise and maps the letters in the corresponding Braille code. Findings: Three Hindi documents containing single, multiple lines are taken as test documents. These test documents are successfully converted into their corresponding Braille code using the proposed algorithm. A lot of research work has been conducted which emphasizes the conversion of scanned Braille code into the text, but the conversion of scanned text to Braille has not been attempted so far. These results are a step further in the field of Braille communication, adding a new way through which Hindi literature can easily be made available to visually impaired people for improving their knowledge and easy access to documents and books as needed. Improvement/Application: The results obtained will provide easy access of Hindi literature to visually challenged people as there is limited availability of Braille textbooks in the market. The memory consumption is very less as the size of each image in Hindi database is 187x128 pixels. This work can be modified for real time applications, like instant conversion of text to Braille using handheld devices.


Hindi Braille, Hindi Data Base, Image Processing, Image Segmentation, Letter Matching, Principal Component Analysis, Text Translation

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  • Chitte PP, Pimpalkar YA, Nair PB, Thombe SA. Braille to text and speech for cecity persons. International Journal of Research in Engineering and Technology. 2015 Jan; 4(1):263–8. Crossref.
  • Al-Shamma SD, Fathi S. Arabic braille recognition and transcription into text and voice. In the Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) 5th Cairo International Biomedical Engineering Conference, Egypt; 2010 Dec 16–18. p. 227–31. Crossref.
  • Wajid M, Abdullah MW, Farooq O. Imprinted braillecharacter pattern recognition using image processing
  • techniques. In the Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) International Conference on Image Information processing, Shimla, India; 2011 Nov 3–5. p. 1–5. Crossref.
  • Proceedings of International Conference on Advanced Computing and Intelligent Engineering. 2015, 2.
  • Isayed S, Tahboub R. A review of optical braille recognition.In the Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) 2nd World Symposium on Web Applications and Networking (WSWAN), Tunisia; 2015 Mar 21–23. p. 1–6. Crossref.
  • Padmavathi S, Manojna KSS, Reddy SS, Meenakshy D.Conversion of braille to text in English, Hindi and Tamil languages. International Journal of Computer Science and Applications. 2013 Jun; 3(3):19–32. Crossref.
  • Parvathi K, Samal BM, Das JK. Odia braille: text transcription via image processing. In the Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) International Conferene on Futuristic Trends on Computational Analysis and Knowledge Management, Noida, Inida; 2015 Feb 25–27. p. 138–43. Crossref.
  • Subbu RS, Gnanaraj P. Enabling visually impaired to read messages from modern gadgets. In the Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) Sixth International Conference on Sensing Technology, Kolkata, India; 2012 Dec 18–21. p. 502–5. Crossref.
  • Rajarapollu P, Kodolikar S, Laghate D, Khavale A.FPGA based braille to text and speech for blind persons.International Journal of Scientific and Engineering Research. 2013 Apr; 4(4):348–53.
  • Hidayat, Prafanto A. Electronic voice for set of the syllables from braille code input based on microcontroller. Indian Journal of Science and Technology. 2016 Dec; 9(47):1–8.Crossref.
  • Halder S, Hasant A, Khatun A, Bhattacharjee D, Nasipuri M. Development of Bangla Character Recognition (BCR) system for generation of bengali text from braille notation.International Journal of Innovative Technology and Exploring Engineering. 2013 Jun; 3(1):5–10.
  • Samal BM, Parvathi K, Das JK. A bidirectional text transcription of braille for odia, hindi, telugu and english via image processing on FPGA. International Journal of Research in Engineering and Technology. 2015 Jul; 4(7):483–94. Crossref.
  • Jariwala NB, Patel B. Conversion of gujarati text into braille: a review. International Journal of Innovation and Advancement in Computer Science. 2015 Jan; 4(1):59–64.
  • Khan K, Ullah R, Khan NA, Naveed K.Urdu character recognition using principal component analysis. International Journal of Computer Applications. 2012 Dec; 60(11):1–4. Crossref.
  • Prasad GK, Khan I,Chanukotimath NR, Khan F. Online handwritten character recognition system for Kannada using principal component analysis approach: for handheld devices. In the Proceedings of the Institute of Electrical and Electronics Engineers (IEEE) World Congress on Information and Communication Technologies, Trivandrum, India; 2012 Oct 30 – Nov 2. p. 675–8.


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