Empowering the visually impaired: A YOLO-v5 CNN-based android app for currency recognition and object detection
1 Adi Shankara Institute of Engineering and Technology, APJ Abdul Kalam Kerala Technological University, Kaladi, Kerala, India, 683574.
2 Mar Baselios Chritian College of Engineering & Technology, APJ Abdul Kalam Kerala Technological University, Kuttikkanam, Peermade, Idukki, Kerala, India 68553.
Research Article
World Journal of Advanced Research and Reviews, 2023, 19(02), 1459–1466
Publication history:
Received on 01 July 2023; revised on 17 August 2023; accepted on 19 August 2023
Abstract:
This paper presents an Android mobile Application (app) that assists people with visual impairments in currency recognition and general object detection. Our project's goal is to assist visually impaired individuals by offering them a practical alternative with a cost-effective solution. The YOLO-v5 CNN model-based currency note detection and object recognition app is proposed for this purpose, and we find it is fast and accurate. The app can identify rupee notes with denominations of 10 new, 10 old, 20 new, 20 old, 50 new, 50 old, 100 new, 100 old, 200, 500, 2000, and general objects such as mobile phones, laptops, chair, water bottle, vehicles, persons, book, door, watch etc.
Keywords:
Currency recognition; General object detection; YOLO-v5; CNN component; Android studio; GitHub; Google Colab.
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Copyright information:
Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0