Fake Currency Detection with Machine Learning Algorithm and Image Processing
Objective
This research aims to distinguish genuine and counterfeit Indian paper currency using image processing techniques. A dataset of original and fake notes is analysed with Support Vector Machine (SVM) for classification, achieving high accuracy
Abstract
Counterfeiting of paper currency is a major issue around the world. Almost every country has been severely impacted by this, which has escalated into a major issue. The major goal of this research is to identify Indian paper currency. We acquired a dataset of the currency notes for both original and fake notes of different denominations from internet. By using feature extraction method of front side of the currency to classify whether the currency is original or fake. In this paper we used the Support Vector Machine (SVM) algorithm for the classification. Perceive whether something is Original or fake. We have used the MATLAB image processing toolbox. Image processing is a method of enhancing an image's visual information for machine or hardware perception. And to classify the denomination of the note we used a SVM and the average accuracy of the trained network with minimal error.
Keywords: - Image Processing, Monetary Identification, Denomination, Currency Identification, Machine learning, SVM.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
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