• Prof. Priyanka Fulsaundar
• Puja Mangale
• Pradnya Ransing
• Ritesh Kadam

The Currency Detection Android Application with Image Processing is an revolutionary answer designed to empower visually impaired people and help tourists in figuring out and handling paper foreign money notes with accuracy and convenience. This software leverages superior photograph processing techniques, inclusive of aspect detection, shadeation analysis, texture recognition, and optical individual recognition (OCR), to extract vital functions from forex notes. Machine learning models, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are employed to recognize currency denominations based on these extracted features. The software affords real-time audio feedback, saying the diagnosed denomination, and capabilities a user-pleasant interface with voice-guided instructions, catering to each visually impaired and sighted users. A comprehensive currency library ensures coverage of major world currencies, with regular updates to accommodate new designs and security features. Offline functionality further enhances accessibility. The project's scope encompasses primary functionalities, target audience, supported currencies, technological considerations, and acknowledges project limitations.

Currency Recognition, Android Application, Image Processing, Machine Learning, Accessibility, Visually Impaired, Travelers, Optical Character Recognition (OCR), Currency Denomination, User Interface, Real-time Exchange Rates, Security Features, Application Development, Offline Mode, Mobile Accessibility, Error Reduction, Financial Independence.

"Currency Recognition Application", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.h306-h310, April-2024, Available :http://www.jetir.org/papers/JETIR2404737.pdf

"Currency Recognition Application", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. pph306-h310, April-2024, Available at : http://www.jetir.org/papers/JETIR2404737.pdf