Currency Detection System for Blind People
Blind or visually impaired individuals encounter challenges in daily life, including difficulty recognizing currency notes. Despite the growing popularity of electronic payments, cash remains widely used. This reliance on cash poses problems for those with visual impairments, as they struggle to identify currency values during financial transactions, making them vulnerable to exploitation. To assist blind individuals Currency Detection System can be employed. This project will include two parts, firstly training of YOLOv8 model on Pakistani currency notes and a system will be employed. The model will be given with an image of a currency note to detect the currency denomination as output. Furthermore, text-to-speech model will be used to convert text output into speech. This Project will be deployed on Google Cloud using NGROK (cross-platform application) enabling the Flask API to be
accessible over the internet. Secondly, it includes research on YOLOv8 and analysis of results obtained by YOLOv8.
Overall, this project aims to empower blind or visually impaired individuals by providing them with a reliable and accessible tool for recognizing currency notes. By leveraging the capabilities of YOLOv8 and text-to-speech technology, the project seeks to improve the independence and financial security of those with visual impairments.
Keywords: Deep Learning,Computer Vision,Cloud Computing
Tools: NGROK,Flask API,Colab Pro
Department: Department of Business Studies
Project Team Members
| Name |
Email |
|
Aqsa Mushtaq
|
aqsamushtaq2020@namal.edu.pk |
Project Poster
