Image-Based Processing of Paper Currency Recognition and Fake Identification: A Review
Sabat Muhamad and
Twana Nasih Ahmed
Additional contact information
Sabat Muhamad: Computer Science Department, Faculty of Science, Soran University, Soran,Erbil, Kurdistan Region, Iraq
Twana Nasih Ahmed: Horticulture and Landscape design Department, Bakrajo Technical institute, Sulaimani Polytechnic University
Technium, 2021, vol. 3, issue 7, 46-63
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.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
https://techniumscience.com/index.php/technium/article/view/4378 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tec:techni:ojs:4378
Access Statistics for this article
Technium is currently edited by Scurtu Ionut Cristian
More articles in Technium from Technium Science
Bibliographic data for series maintained by Ana Maria Golita ().