Indian currency identification for visually impaired persons with audio output using a CNN algorithm is a technology designed to enhance the independence and quality of life of visually impaired individuals in India. The system recognises and identifies various denominations of Indian rupee by using a machine learning model trained on images of Indian cash. The CNN algorithm can analyse photos captured by a camera, such as those from a smartphone or other device, and differentiate various denominations of currency, such as 10 rupees, 50 rupees, etc. The system uses audio output in which the denomination of the money is read aloud to the user, hence aiding visually handicapped individuals in identifying and recognising Indian cash. The technology is compatible with mobile applications and smart devices. This technology is still in its developmental stages, but it has the ability to change the lives of visually impaired individuals in India. Even though, the technology presents a number of challenges, including lighting conditions, picture clarity, and the many variances of Indian rupee notes. The study tries to overcome these obstacles and improve the robustness and dependability of the technology.
Index Terms—Neural networks, Machine learning, Assistive technology, Image processing, Visually impaired.