Currency Detection for the Visually Impaired Using Deep Learning

The model utilizes MobileNet V2 that has been trained using a diversified banknote image dataset recorded under different real-world environments, both robust and accurate. The model is TensorFlow Lite optimized and run on a Raspberry Pi for best-in-class edge inference. Real images are captured by a camera module, classified by the CNN, and the output is transmitted using a text-to-speech engine for auditory feedback. The system is off-line based and therefore portable and internetindependent. Its small size, low price, and high precision make it perfect for mass usage, particularly in developing regions. Experimental validation verifies that the system behaves uniformly in multiple lighting and occlusion conditions, highlighting its ability to uplift the blind community to greater economic security.