Automated Electronic Pen Aiding Visually Impaired in Reading, Visualizing and Understanding Textual Contents

Author:

Joshi Kumar A.V.1,Madhan Prabhu T.1,Mohan Raj S.1

Affiliation:

1. Sri Sairam Engineering College

Abstract

Blindness is an obstacle that is not even comprehendible for the non-blind. Many day-to-day activities may become challenging, complicated and may require much more labor for those with eye-sight problems or blindness. One of the major problems they face is understanding visual or text information which are not in the Braille form. Not every written or printed document that a blind person would like to read is available in Braille. A blind cannot read any of the handwritten documents. They feel it very difficult, while someone has to read it for them. This is the fundamental issue that we deal with, and try to solve, with a new piece of technology, which is essentially an automated text-to-audio converting pen. According to this keynote concept, any piece of text that a person would like to read/understand is converted to an audio signal. This audio signal is transmitted to the person’s ears through wireless technology such as Bluetooth. Since this technology is in the form of a pen, it is very convenient to use and is also portable. This instrument is radical and can definitely be a empowering force in a blind person’s life, and can be helpful in relieving them of their frustration of not being able to read whatever they want, thus making their life easier.

Publisher

Trans Tech Publications, Ltd.

Subject

General Engineering

Reference8 articles.

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2. Information on http: /www. afb. org/section. asp?SectionID=6.

3. Information from http: /www. aip. org/dbis/stories/2008/18052. html.

4. C´ elineMancas-Thillou, Silvio Ferreira, Jonathan Demeyer, ChristopheMinetti, and Bernard Gosselin A Multifunctional Reading Assistant for the Visually Impaired, in Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2007, Article ID 64295, 11 pages doi: 10. 1155/2007/6429.

5. Kenichiro Kigo Improving Speed of Japanese OCR through Linguistic Preprocessing.

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