Complex Support System for Visually Impaired Individuals
Keywords
visually impaired, support system, object detection, deep learningAbstract
It is very difficult for visually impaired individuals to avoid obstacles, to notice or recognize obstacles in distance, to notice and follow the special paths made for them. They continue their lives by touching these situations or finding solutions with the help of a walking stick in their hands. Due to these safety problems, it is difficult for visually impaired individuals to move freely and these situations affect individuals negatively in terms of social and health. In order to find solutions to these problems, a support system has been proposed for visually impaired individuals. The vision support system includes an embedded system with a camera with an audio warning system so that the visually impaired individual can identify the objects in front of him, and a circuit with an ultrasonic sensor so that he can detect the obstacles in front of him early and take precautions. The object recognition system is realized with convolutional neural networks. The Faster R-CNN model was used and in addition to this, a model that we created, which can recognize 25 kinds of products, was used. With the help of the dataset we created and the network trained with this dataset, the visually impaired individual will be able to identify some market products. In addition to these, auxiliary elements were added to the walking sticks they used. This system consists of a camera system that enables the visually impaired individual to notice the lines made for the visually impaired in the environment, and a tracking circuit placed at the tip of the cane so that they can easily follow these lines and move more easily. Each system has been designed separately so that the warnings can be delivered to the visually impaired person quickly without delay. In this way, the error rate caused by the processing load has been tried to be reduced. The system we have created is designed to be wearable, easy to use and low-cost to be accessible to everyone.
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Published: 2022-09-17
Issue: Vol. 1 No. 1 (2022) (view)
Section: Research Articles
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