TELKOMNIKA Telecommunication, Computing, Electronics and Control
Development smart eyeglasses for visually impaired people based on you only look once
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Development smart eyeglasses for visually impaired people based on you only look once
Development smart eyeglasses for visually impaired people based on you only look once
Subject
Computer vision, Convolutional neural network, Object detection, OpenCV, YOLO
Description
Visually impaired people are facing many problems in their life. One of
these problems is how they can find the objects in their indoor environment. This research was presented to assists visually impaired people in finding the objects in office. Object detection is a method used to detect the objects in images and videos. Many algorithms used for object detection such as convolutional neural network (CNN) and you only look once (YOLO). The proposed method was YOLO which outperforms the other algorithms such as CNN. In CNN the algorithm splits the image into regions. These regions sequentially enters the neural network for object detection and recognition so CNN does not deal with all the regions at the same time but YOLO looks the entire image then it produces the bounding boxes with convolutional network and the probabilities of these boxes, this makes YOLO faster than other algorithms. Open source computer vision (OpenCV) used to capture frames by using camera. Then YOLO used to detect and recognize the
objects in each frame. Finally, the sound in Arabic language was generated to tell the visually impaired people about the objects. The proposed system can detect 6 objects and achieve an accuracy of 99%.
these problems is how they can find the objects in their indoor environment. This research was presented to assists visually impaired people in finding the objects in office. Object detection is a method used to detect the objects in images and videos. Many algorithms used for object detection such as convolutional neural network (CNN) and you only look once (YOLO). The proposed method was YOLO which outperforms the other algorithms such as CNN. In CNN the algorithm splits the image into regions. These regions sequentially enters the neural network for object detection and recognition so CNN does not deal with all the regions at the same time but YOLO looks the entire image then it produces the bounding boxes with convolutional network and the probabilities of these boxes, this makes YOLO faster than other algorithms. Open source computer vision (OpenCV) used to capture frames by using camera. Then YOLO used to detect and recognize the
objects in each frame. Finally, the sound in Arabic language was generated to tell the visually impaired people about the objects. The proposed system can detect 6 objects and achieve an accuracy of 99%.
Creator
Hassan Salam Abdul-Ameer, Hassan Jaleel Hassan, Salma Hameedi Abdullah
Source
DOI: 10.12928/TELKOMNIKA.v20i1.22457
Publisher
Universitas Ahmad Dahlan
Date
February 2022
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Hassan Salam Abdul-Ameer, Hassan Jaleel Hassan, Salma Hameedi Abdullah, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Development smart eyeglasses for visually impaired people based on you only look once,” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/4275.
Development smart eyeglasses for visually impaired people based on you only look once,” Repository Horizon University Indonesia, accessed September 20, 2024, https://repository.horizon.ac.id/items/show/4275.