An intelligent system for paper currency recognition with robust features

Abstract

Intelligent systems on Paper currency recognition and verification are inevitable for modern banking services. These systems are used in Auto-seller machines, vending machines etc. Extracting sufficient and reliable monetary characteristics are essential for accuracy and performance of such systems. This paper proposes a new intelligent system for paper currency recognition. Pakistani paper currency has been considered, as a case study, for intelligent recognition. This paper identifies, introduces, and extracts robust features from Pakistani banknotes. After extracting these features, the paper proposes to use three layers feed-forward Backpropagation Neural Network (BPN) for intelligent classification. The proposed technique and system are simple and comparatively less time consuming which makes it suitable for real-time applications. In order to evaluate the performance of the proposed technique, experiments have been conducted on 175 Pakistani banknotes. The results indicate that system has 100% recognition ability on properly captured images.