Abstract:
Recognizing monetary notes is simple for a normal person, but it is not so for a visually impaired
individual. A visually impaired person is someone who has either a partial or complete loss of
vision. They face numerous challenges in their daily lives, including monetary interactions. Due
to the similarity in paper texture and size ofdifferent types ofcurrency notes, they have difficulties
distinguishing between them. Institutions like as banks can afford expensive technology to address
the issue of currency recognition, but the general public, particularly the visually challenged,
cannot. The goal ofthis project is to assist such individuals and provide a cost-effective solution.
This project proposes the creation of a money detection software that will aid in the identification
of Pakistani currency notes. Based on Convolutional Neural Networks, we proposed a system for
blind or visually impaired people to detect Pakistani cash (CNN). Seven different Pakistani paper
currency notes (Rs.10, 20, 50, 100, 500, 1000, and 5000) are used for training and testing in the
proposed system. This system, which will be implemented using image processing techniques and
will be deployed as an Android application, will aid in the identification ofmoney notes.
