Efficient Conversion of Handwritten Text to Braille Text for Visually Challenged People

  • M. AnithaEmail author
  • D. Elangovan
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)


The World Health Organization has submitted a report in 2017 which declared that a population of nearly 36 million people are blind out of 253 million visually impaired people. Braille books in the tactile format are very helpful for the visually impaired people to gain knowledge but the availability of these resources is limited. With the improvement of electronic innovation, Braille ended up being appropriate to PC helped generation in light of its coded structures. Programming based content to-Braille interpretation has been ended up being a fruitful arrangement in Assistive Innovation. Various research studies and papers describe the methods for obtaining machine readable document from textual image. In future, character recognition might serve as a key role to create a paperless environment that helps the visually impaired people to gain enormous amount of educational materials. In current world the innovations and advancements in modern scientific systems has expanded the boundaries of human effort like Optical Character Recognition. In the field of machine learning and pattern matching Handwritten recognition has gained lot of attention. A novel method is proposed to convert Handwritten text into Braille text due to which huge resources of Handwritten text materials will be available in Braille text that helps the visually impaired and low vision people to expand their knowledge. The novelty of this system has gained a better accuracy.


Braille Handwritten Optical Character Recognition Visually impaired 


  1. 1.
    Nahar, L., Jaafar, A., Ahamed, E., Kaish, A.B.M.A.: Design of a Braille learning application for visually impaired students in Bangladesh. Off. J. RESNA 27(3), 172–182 (2015)Google Scholar
  2. 2.
    Russomanno, A., O’Modhrain, S., Gillespie, R.B., Rodger, M.W.: Refreshing refreshable braille displays. IEEE Trans. Hapt. 8(3), 287–297 (2015). Scholar
  3. 3.
    Sultana, S., Rahman, A., Chowdhury, F.H., Zaman, H.U.: A novel Braille pad with dual text-to-Braille and Braille-to-text capabilities with an integrated LCD display. In: 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, pp. 195–200 (2017)Google Scholar
  4. 4.
    O’Modhrain, S., Giudice, N.A., Gardner, J.A., Legge, G.E.: Designing media for visually-impaired users of refreshable touch displays: possibilities and pitfalls. IEEE Trans. Hapt. 8(3), 248–257 (2015)CrossRefGoogle Scholar
  5. 5.
    Kala, R., Vazirani, H., Shukla, A., Tiwari, R.: Offline handwriting recognition using genetic algorithm. IJCSI Int. J. Comput. Sci. Issues 7(2, 1) (2010)Google Scholar
  6. 6.
    Wshah, S., Kumar, G., Govindaraju, V.: Statistical script independent word spotting in offline handwritten documents. Pattern Recog. 47(3), 1039–1050 (2014)CrossRefGoogle Scholar
  7. 7.
    Plamondon, R., Srihari, S.N.: On-line and off-line handwritten character recognition: a comprehensive survey. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 63–84 (2000)CrossRefGoogle Scholar
  8. 8.
    Kumar, M., Jindal, M.K., Sharma, R.K., Jindal, S.R.: Offline handwritten numeral recognition using combination of different feature extraction techniques. Natl. Acad. Sci. 41(1), 29–33 (2018)CrossRefGoogle Scholar
  9. 9.
    Venugopal, V., Sundaram, S.: Online writer Identification with sparse coding based descriptors. IEEE Trans. Inf. Forensics Secur. 13(10), 2538–2552 (2018)CrossRefGoogle Scholar
  10. 10.
    Tavoli, R., Keyvanpourv, M.: A method for handwritten word spotting based on particle swarm optimisation and multi-layer perceptron. IET Softw. 12(2), 152–159 (2018)CrossRefGoogle Scholar
  11. 11.
    Bawane, P., Gadariye, S., Chaturvedi, S., Khurshid, A.A.: Object and character recognition using spiking neural network. In: International Conference on Processing of Materials, Minerals and Energy, vol. 5, no. 1, Part 1, pp. 360–366 (2018)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science and EngineeringPanimalar Engineering CollegeChennaiIndia

Personalised recommendations