Engineering and Technology Journal

Blind Assistive System based on Real Time Object Recognition using Machine learning

Authors

Control and Systems Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.

Abstract

Healthy people carry out their daily lives normally, but the visually impaired and the blind face difficulties in practicing their daily activities safely because they are ignorant of the organisms surrounding them.  Smart systems come as solutions to help this segment of people in a way that enables them to practice their daily activities safely as possible.  Blind assistive system using deep learning based You Only Look Once algorithm (YOLO) and Open CV library for detecting and recognizing objects in images and video streams quickly. This work implemented using python. The results gave a satisfactory performance in detecting and recognizing objects in the environment. The results obtained are the identification of the objects that the Yolo algorithm was trained on, where the persons, chairs, oven, pizza, mugs, bags, seats, etc. were identified.

Highlights

  • A system that helps blind people discover the objects around them using one of the deep learning algorithms called Yolo. 
  • The system consists of two parts: the software, represented by the Yolo algorithm, and the hardware part is the Raspberry Pi.
  • The proposed system is characterized by high accuracy and good speed.

Keywords

Main Subjects

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Engineering and Technology Journal
Volume 40, Issue 1
Mechanical Engineering
, 33 articles
January 2022
Page 159-165
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