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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 5, 2022.
Abstract: Object recognition method is a computer vision technique for identifying objects in images. The main purpose of this system build is to put an end to blindness by constructing automated hardware with Raspberry Pi that enables a visually impaired person to detect objects or persons in front of them instantly, and inform what is in front of them through audio. Raspberry Pi receives data from a camera then processes it. In addition, the blind will listen to a voice narration via an audio receiver. This paper’s key objective is to provide the blind with cost-effective smart assistance to explore and sense the world independently. The second objective is to provide a convenient portable device allows users to recognise objects without touch, having the system determine the object in front of them. The camera module attached in Raspberry Pi will capture image and the processor will then process it. Subsequently, the processed image sends data to the audio receiver narrating the detected object(s). This system will be very useful for a blind person to explore the world by listening to the voice narration. The generated voice narration after processing the image will help the blind to visualise objects in front of them.
Jamil Abedalrahim Jamil Alsayaydeh, Irianto, Maslan Zainon, Hasvinii Baskaran and Safarudin Gazali Herawan, “Intelligent Interfaces for Assisting Blind People using Object Recognition Methods” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130584
@article{Alsayaydeh2022,
title = {Intelligent Interfaces for Assisting Blind People using Object Recognition Methods},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130584},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130584},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {Jamil Abedalrahim Jamil Alsayaydeh and Irianto and Maslan Zainon and Hasvinii Baskaran and Safarudin Gazali Herawan}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.