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Automatic Recognition and Counterfeit Detection of Ethiopian Paper Currency
Author(s) -
Jegnaw Fentahun Zeggeye,
Yaregal Assabie
Publication year - 2016
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2016.02.04
Subject(s) - computer science , artificial intelligence , computer vision , segmentation , face (sociological concept) , counterfeit , video tracking , encoding (memory) , object class detection , region of interest , object (grammar) , face detection , viola–jones object detection framework , facial recognition system , pattern recognition (psychology) , geography , social science , archaeology , sociology
Currency recognition is a technology used to identify currencies of various countries. The use of automatic methods of currency recognition has been increasing due its importance in many sectors such as vending machine, railway ticket counter, banking system, shopping mall, currency exchange service, etc. This paper describes the design of automatic recognition of Ethiopian currency. In this work, we propose hardware and software solutions which take images of an Ethiopian currency from a scanner and camera as an input. We combined characteristic features of currency and local feature descriptors to design a four level classifier. The design has a categorization component, which is responsible to denominate the currency notes into their respective denomination and verification component which is responsible to validate whether the currency is genuine or not. The system is tested using genuine Ethiopian currencies, counterfeit Ethiopian currencies and other countries’ currencies. The denomination accuracy for genuine Ethiopian currency, counterfeit currencies and other countries’ currencies is found to be 90.42%, 83.3% and 100% respectively. The verification accuracy of our system is 96.13%.

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