Abstract

The main purpose of this study is to propose a method that could recognize the Pakistani paper currency note. There are many real-life applications which heavily use many techniques based on Pattern Recognition such as voice recognition, character recognition, handwriting recognition and face recognition. Paper currency recognition is a new application of pattern recognition. This application uses the computing power in differentiating between different kinds of currencies with their suitable class. Selection of proper feature enhanced the performance of the overall system. We are aiming to develop an intelligent system for Pakistani paper currency that could recognize the currency note accurately. In this study, we have taken samples domain of five different Pakistani paper currency notes (Rs. 10, 20, 50, 100, 1000). We scanned total 100 currency notes, 20 from each sample of selected domain for feature extraction of these images using a software. The images will be matched with the features stored in MAT file and if the features of test images will be matched with that file, the software will return the class of that currency note. Experimental results are presented which show that this scheme can recognize currently available 8 notes of Pakistan’s Currency (Rs. 10, 20, 50, 100, 500, 1000 etc.) successfully with an average accuracy of 98.57%.

Keywords:

Feature extraction, Pakistan currency, recognition system,

References

Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.