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

Kadhim, Mais R.; Oleiwi, Bushra K.

doi:10.30684/etj.v40i1.1933

	Blind Assistive System based on Real Time Object Recognition using Machine learning
Engineering and Technology Journal
Article 18, Volume 40, Issue 1, January 2022, Pages 159-165 PDF (703.14 K)
DOI: 10.30684/etj.v40i1.1933
Authors
Mais R. Kadhim^* ; Bushra K. Oleiwi
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
Objects detection; Open CV; Python; YOLO; Deep neural network

References
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