Computer vision based currency classification system


There are numerous problems associated with current system which are solving the problem of automatic currency classification. Some of the problems administered are like scaling, rotation and noise in the form of missing valuable data in printing or due to the wear and tear of currency notes. In our system we are first aligning the image horizontally along the x axis and after that foreground of the image is removed by detecting the location of edges, and once we have got the processed image we can apply any of the techniques for classification. Over here we are using fast template matching for recognizing the value of the currency. Once we get result after template matching we can classify the currency into different categories like 10, 50,100,500 and 1000. In our system we are aiming at the improvement on existing system by adding useful and robust pre-processing techniques which has been missing in most of the recent works done so far.

Cite this paper

@inproceedings{Singh2011ComputerVB, title={Computer vision based currency classification system}, author={Bhupendra Singh and Pankaj Badoni and Kuldeep Verma and Bazil Shaik and Sandhya Srinivasan}, year={2011} }