Iranian cashes recognition using mobile

TL;DR

This paper presents a mobile-based system that uses image processing and machine vision to recognize the monetary value of cash notes with high accuracy, aiding visually impaired individuals in everyday transactions.

Contribution

It introduces a fast, mobile-compatible approach for cash recognition that handles various challenges like rotation, scaling, and lighting changes with about 95% accuracy.

Findings

Achieved approximately 95% recognition accuracy.

Effectively handled rotation, scaling, and illumination variations.

Provided a practical tool for visually impaired users.

Abstract

In economical societies of today, using cash is an inseparable aspect of human life. People use cashes for marketing, services, entertainments, bank operations and so on. This huge amount of contact with cash and the necessity of knowing the monetary value of it caused one of the most challenging problems for visually impaired people. In this paper we propose a mobile phone based approach to identify monetary value of a picture taken from cashes using some image processing and machine vision techniques. While the developed approach is very fast, it can recognize the value of cash by average accuracy of about 95% and can overcome different challenges like rotation, scaling, collision, illumination changes, perspective, and some others.