Eroded money notes recognition using wavelet transform

Process of bank checks and money notes play an important role in today commercial society. Usually automatic teller machines (ATM) have problems with eroded money notes. In this paper we proposed a new method for worn out Farsi money notes recognition using their texture content and wavelet transform. First, with the help of face detection algorithm, the obverse of the money note is separated from its reverse side. Then, central part of the money note, containing texture is extracted. Finally, wavelet transform is applied to this region of interest (ROI) to extract some features. Some distance measures are utilized to classify the input money note into predefined groups according to minimum distance. To increase accuracy of the system, in the post processing step, we used courtesy amount of the money note and template matching technique. The experimental results have shown that system performance is 80% for eroded money notes recognition.