International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

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DOI Prefix: 10.47001/IRJIET

Online Blind Assistive System using Object Recognition

Abdul Muhsin MControl and Systems Engineering Department, University of Technology, IraqFarah F. AlkhalidControl and Systems Engineering Department, University of Technology, IraqBashra Kadhim OleiwiControl and Systems Engineering Department, University of Technology, Iraq

Vol 3 No 12 (2019): Volume 3, Issue 12, December 2019 | Pages: 47-51

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 21-12-2019

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Abstract

Everybody deserve to live independently, especially those who disabled, with the last decades, technology gives attention to disabled to make them control their life as possible. In this work, assistive system for blind is suggested, to let him knows what is around him, by using YOLO for detecting objects within images and video streams quickly based on deep neural network to make accurate detection, and OpenCV under Python using Raspberry Pi3. The obtained results indicated the success of the proposed model in giving blind users the capability to move around in unfamiliar indoor outdoor environment, through a user friendly device by person and object identification model.

Keywords

Object detection, YOLO, Deep neural network, OpenCV, Python, Raspberry Pi3


Citation of this Article

Abdul Muhsin M, Farah F. Alkhalid, Bashra Kadhim Oleiwi, “Online Blind Assistive System using Object Recognition” Published in International Research Journal of Innovations in Engineering and Technology (IRJIET), Volume 3, Issue 12, pp 47-51, December 2019.

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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