Real-time input text recognition system for the aid of visually impaired

Abstract

It is estimated that 285 million people globally are visually impaired. A majority of these people live in developing countries and are among the elderly population. Reading is essential in daily life for everyone. Visually impaired persons can read only by use of special scripts specially designed for them such as Braille language. Further, only trained people can read and understand. Since every product does not provide the product information on product cover in Braille, the present work proposes an assistive text reading framework to help visually impaired persons to read texts from various products/objects in their daily lives. The first step in implementation captures the image of the required by extracting frames from real-time video input from the camera. This is followed by preprocessing steps which includes conversion to grey scale and filtering. The text regions are further extracted using MSER followed by canny edge detection. The text regions from the captured image are then extracted and recognized by using Optical Character Recognition software (OCR). The OCR engine Tesseract is used here. This extracts the text of various fonts and then sizes can be recognized individually and then combined to form a word. Further, producing audio output by using Text to Speech module. The result obtained is very much comparable with other existing methods with better time efficiency. The real-time input is taken and passed through the algorithm which applies filters and removes noise then later image is passed through MSER, OCR, Canny edge detection to get the final audio output.