Abstract
Visual impairment is a major crisis for visually impaired people (VIP) and consequently, VIP require keen guidance to perform their regular activities. This paper develops a smartphone-based object (e.g. currency note, staircase, etc.) recognition system that can alleviate the monetary transactions, mobility issues, etc. for VIP. Due to the usage of a singular smartphone, the design of the system remains straightforward, and it requires no extra hardware. Alongside, it is convenient to adapt to the human body. Then, to recognize the object in real-time, it exploits Single Shot Detector (SSD), Convolutional Neural Network (CNN), and Tensorflow-lite (tflite) that classifies, train as well as test the object, and supports the platform, respectively for this purpose. First, it creates a dataset in the format of the COCO dataset. Then, it labels the recognized object by a text to speech conversion method and sends it to the VIP via Bluetooth technology. The experimental results show that for object recognition and detection, the accuracy of the developed system is 94.25% and 98.23%, respectively that outperforming the existing systems. Moreover, it uploads all processed data to a remote server. Overall, the proposed system uses audio messages to guide the VIP in recognizing currency notes and avoiding obstacles in their surroundings.
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