Fake Banknotes Classification Using Wavelet and Anfis Topology Based on Vision

today, the volume of transactions is increasing and some people in the communities of their money exchanges use fraud banknote which is a crime and it is illegally and brings a lot of damage economically. Diagnosis of this fake banknote, is a serious challenge. We presented proposed approach in this...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of computer science and information security Vol. 14; no. 8; p. 126
Main Authors Iraji, Mohammad Saber, Moghadam, Saeid Anjakani
Format Journal Article
LanguageEnglish
Published Pittsburgh L J S Publishing 01.08.2016
Subjects
Accuracy
Adaptive systems
Banking
Banknotes
Classification
Counterfeiting
Datasets
Economics
Exchange
Financial institutions
Financial services
Fraud
Fuzzy logic
Fuzzy sets
Fuzzy systems
Genetic algorithms
Mean square errors
Methods
Neural networks
R&D
Research & development
Topology
Vision
Wavelet
Online AccessGet full text
ISSN1947-5500

Cover

More Information
Summary:today, the volume of transactions is increasing and some people in the communities of their money exchanges use fraud banknote which is a crime and it is illegally and brings a lot of damage economically. Diagnosis of this fake banknote, is a serious challenge. We presented proposed approach in this paper to predicate fake banknote's class than the actual class and calculate the correct classification index, through adaptive neuro fuzzy system (ANFIS) Method based on wavelet features with vision sensing which indicate better and more accurate results 100% in comparison other methods.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:1947-5500