An Efficient Technique for Detection of Fake Currency

Author:

Abstract

During the past years, some of the researchers are using the matching techniques for identification of the fake currency either by using the Mathematical formulation or by using the readymade simulation tools. A lot of methods namely edge detection, segmentation, feature extraction, pattern matching has been used for finding and identification of the fake currency. In the present work, Principal Component Analysis (PCA) is used to detect the feature of currency through modeling and a proposed algorithm is elaborated to recognize the fake currency in the form of note Rs 2000 of Indian currency. Graphs are also designed to justify the present approach along with the comparison of results

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Management of Technology and Innovation,General Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Counterfeit Currency Detection and Recognition for Blind People;International Journal of Advanced Research in Science, Communication and Technology;2023-11-19

2. Fake Currency Note Recognition using Extreme Learning Machine;2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2023-05-04

3. Malaysian Banknotes Counterfeit Detection Algorithm for Fifty Ringgit and One-hundred Ringgit;2022 International Visualization, Informatics and Technology Conference (IVIT);2022-11-01

4. Malaysian Banknotes Counterfeit Detection Algorithm for Ten Ringgit and Twenty Ringgit;2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS);2022-06-25

5. Texture Feature Technique for Security of Indian Currency;Lecture Notes in Electrical Engineering;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3