Development smart eyeglasses for visually impaired people based on you only look once - Hassan Salam Abdul-Ameer; Hassan Jaleel Hassan; Salma Hameedi Abdullah (TELKOMNIKA (Telecommunication Computing Electronics and Control), 2022)
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%.