Image-Based Processing of Paper Currency Recognition and Fake Identification: A Review

Abstract

There are over 180 different currencies on the globe. Each currency is distinct in terms of scale, paper, colors, patterns, text, etc. It is tough to keep track of all of the different currencies. Often, determining whether a currency is genuine or counterfeit is challenging. Many methods investigate currency recognition. In this review, the following techniques are widely used in image processing for currency recognition tools, including acquisition, image enhancement, segmentation, and object detection and recognition. This review shows the ability of image processing techniques, including pre-processing, edge detection, feature extraction, and thresholding, to recognize paper currency have been used. Thus, the outcome of this review indicates that for currency recognition the techniques that used for feature extraction are (LBP, SIFT, SURF and ROI) and choosing the best technique depends on the application.