relation: https://digilib.uin-suka.ac.id/id/eprint/22545/
title: A Counterfeit Paper Currency Recognition System  Using LVQ based on UV Light
creator: Harjunowibowo, Dewanto
creator: Hartati, Sri
creator: Budianto, Aris
subject: Sains
description: This research is aimed to test a paper currency  counterfeit detection system based on Linear Vector  Quantization (LVQ) Neural Network. The input image of the  system is the dancer object image of paper currency Rp. 50.000,-  fluorescent by ultraviolet light. The image of paper currency data  was taken from conventional banks. The LVQ method is used to  recognize whether the paper currency being tested is counterfeit  or not. The coding was carried out using visual programming  language. The feature size of the dancer tested object is 114x90  px and the RGBHSI was extracted as the input for LVQ. The  experimental results show that the system has an accuracy 100%  of detecting 20 real test case data, and 96% of detecting 22  simulated test case data. The simulated case data was generated  by varying the brightness of the image data. The real test case  data contains of 10 counterfeit paper currency and 10 original  paper currency. The simulated case data contains of 11 original  paper currency and 11 counterfeit paper currency. The best  setting for the system is Learning Rate = 0.01 and MaxEpoh =  10.  Keywords-CRM 2.0; detection system, counterfeit paper  currency, neural network, LVQ, digital image processing
publisher: Fakultas Sains dan Teknologi
date: 2012-02-02
type: Article
type: PeerReviewed
format: text
language: en
identifier: https://digilib.uin-suka.ac.id/id/eprint/22545/1/Dewanto%20Harjonowibowo%20-%20A%20Counterfeit%20Paper%20Currency%20Recognition%20System.pdf
identifier:   Harjunowibowo, Dewanto and Hartati, Sri and Budianto, Aris  (2012) A Counterfeit Paper Currency Recognition System Using LVQ based on UV Light.  IJID (International Journal on Informatics for Development), Vol.1 (No. 2).  pp. 9-13.  ISSN 2252-7834