Real-Time Currency Detection and Voice Feedback for Visually Impaired Individuals
Saraf Anzum Shreya, MD. Abu Ismail Siddique, Sharaf Tasnim

TL;DR
This paper presents a real-time currency detection system using YOLOv8 nano and voice feedback to assist visually impaired individuals in identifying multiple currencies with high accuracy.
Contribution
It introduces a novel deep learning model with a custom detection head for accurate, real-time currency recognition tailored for visually impaired users.
Findings
Achieved 97.73% detection accuracy
High recall and F1-score for currency detection
Effective voice feedback implementation
Abstract
Technologies like smartphones have become an essential in our daily lives. It has made accessible to everyone including visually impaired individuals. With the use of smartphone cameras, image capturing and processing have become more convenient. With the use of smartphones and machine learning, the life of visually impaired can be made a little easier. Daily tasks such as handling money without relying on someone can be troublesome for them. For that purpose this paper presents a real-time currency detection system designed to assist visually impaired individuals. The proposed model is trained on a dataset containing 30 classes of notes and coins, representing 3 types of currency: US dollar (USD), Euro (EUR), and Bangladeshi taka (BDT). Our approach uses a YOLOv8 nano model with a custom detection head featuring deep convolutional layers and Squeeze-and-Excitation blocks to enhance…
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Taxonomy
TopicsCurrency Recognition and Detection · Digital Media Forensic Detection · Blockchain Technology Applications and Security
