Feature extraction and identification of Indian currency notes

Banknote identification systems, with their wide applications in Automated Teller Machines (ATMs), vending machines and currency recognition aids for the visually impaired, are one of the most widely researched fields today. The present paper proposes a novel technique for recognition of Indian currency banknotes by adopting a modular approach. The proposed work extracts distinct and unique features of Indian currency notes such as central numeral, RBI seal, colour band and identification mark for the visually impaired and employs algorithms optimized for the detection of each specific feature. The proposed technique has been evaluated over a large data set for recognition of Indian banknotes of various denominations and physical conditions including new notes, wrinkled notes and non-uniform illumination. Thorough analysis yields a high true positive rate (desired feature identified correctly) of 95.11% and a low false positive rate (undesired feature recognition minimized) of 0.09765% for emblem recognition, an accuracy of 97.02% for central numeral detection, and 100% accuracies for both recognition of identification mark and colour matching in CIE LAB colour space.