A Novel Method for Banknote RecognitionSystem

The purpose of currency recognition system is to categorize the currencies accurately. In this work, banknotes are recognized using a novel feature extraction technique such as speeded up robust features (SURF) which is a combination of both interest point detector and descriptor. Speeded up robust features are used to extract the local image features of an image. The SURF features extracted are both scale and rotation invariant which makes it robust against various image transformations. The interest points are detected from the test and the template images followed by SURF feature extraction. Then the distance between the SURF descriptors for corresponding matched interest points is calculated and the average distance is taken to find the category of the banknote. The proposed system is evaluated on the dataset and achieves high recognition rate.

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