Image Acquisition and Text To Speech Conversion for Visually Impaired People

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Author(s) Priyanka Rathod | Suvarna Nandyal
Pages 253-259
Volume 6
Issue 8
Date August, 2016
Keywords Binarization, Segmentation, Templates, Optical Character Recognition (OCR), Text-To-Speech.


In today’s world, many people are facing problems due to disability in sense organs such as low eye sight, hearing issues, and many other problems. There are nearly about 161 million visually impaired and 37 million blind people worldwide. Many times they are confused in a new environment because of communication and access to information. It becomes tedious for blind people to read and walk to know the shop around due to visually impaired. Hence objective of the proposed work is to detect, extract and recognize text from images and convert them into text to speech. The work presents an algorithm for implementation of Optical Character Recognition (OCR) to translate images with standard labels with standard font sizes, into electronically editable format and then to speech to assist visually impaired users. OCR can do this by applying pattern matching algorithm the recognized character are stored in editable format. Thus OCR makes the computer read input image text label discarding noise. Image detection and extraction is done using OCR algorithm, then the extracted text of the image is converted to actually text using cross correlation algorithm. Then finally text is converted to speech/audio through the mobile via remotely.

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