Work

Thai Currency Classification Application for Visually Impaired Persons

Year: 2024

Type: article

Abstract: This research presents an application designed to assist visually impaired individuals in identifying Thai banknotes and coins. The application utilizes image processing and machine learning techniques, specifically a Convolutional Neural Network with ResNet101 architecture, to accurately classify 11 types of Thai currency. It is designed for offline use on smartphones, providing real-time audio and text output to enhance accessibility and understanding for users with visual impairments. The dataset includes 2,593 images of Thai banknotes and coins, split into 80% for training and 20% for testing. The application employs the trained model to conduct real-world tests using a smartphone camera, testing with actual banknotes and coins, achieving an average accuracy of 92.73%.

Source: Journal of Current Science and Technology

DOI: 10.59796/jcst.v14n3.2024.64

Authors: Wiyada Yawai, Mongkol Saejia, Nuntiya Limsiroratana, Rujirawadee Thammasang

Institutions: Nakhon Ratchasima Rajabhat University, Prince of Songkla University, Nakhon Pathom Rajabhat University

Language: English

Topic: Currency Recognition and Detection

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Reduced inequalities

Open Access status: diamond

OpenAlex ID: W4402114897

FWCI: 0.432

Cites: 17

Cited by: 3

Related to: 10