Reading Assistant for Visually Challenged Peoples with Advance Image Capturing Technique Using Machine Learning

Abstract

Since blindness prevents a person from learning about their surroundings, it is difficult for them to independently navigate, recognise items, avoid hazards, and read. In this essay, we provide a ground-breaking system for visually impaired people who use assistive technology. The concept incorporates a camera, sensors, and effective image processing algorithms that use Raspberry Pi for object detection and obstacle avoidance. Ultrasonic sensors and the camera both measure the user's distance from the obstruction. The system consists of integrated reading help that first generates an audio response before converting images to text. The complete apparatus is small and light, and it can be easily and inexpensively mounted on a regular pair of eyeglasses. The entire system is affordable, easy to use, and can be attached to a regular pair of eyeglasses. It is also portable and lightweight. Ten people who are completely blind will be used to compare the performance of the suggested device to the traditional white cane. The evaluations are conducted in controlled environments intended to mimic day-to-day activities for blind persons. The findings show that the proposed device provides more accessibility, comfort, and simplicity of navigation for the blind when compared to the white cane.