This paper is published in Volume-4, Issue-2, 2018
Area
Computer Science
Author
Gouri Sanjay Tele
Co-authors
Akshay Prakash Kathalkar, Sneha Mahakalkar, Bharat Sahoo, Vaishnavi Dhamane
Org/Univ
Datta Meghe Institute of Engineering Technology and Research, Wardha, Maharashtra, India
Pub. Date
14 March, 2018
Paper ID
V4I2-1173
Publisher
Keywords
MATLAB, Image Processing, Currency, Feature Extraction, Pre-Processing, Edge Detection, CNN, SURF

Citationsacebook

IEEE
Gouri Sanjay Tele, Akshay Prakash Kathalkar, Sneha Mahakalkar, Bharat Sahoo, Vaishnavi Dhamane. Detection of Fake Indian Currency, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Gouri Sanjay Tele, Akshay Prakash Kathalkar, Sneha Mahakalkar, Bharat Sahoo, Vaishnavi Dhamane (2018). Detection of Fake Indian Currency. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.

MLA
Gouri Sanjay Tele, Akshay Prakash Kathalkar, Sneha Mahakalkar, Bharat Sahoo, Vaishnavi Dhamane. "Detection of Fake Indian Currency." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.

Abstract

Fake currency detection is a serious issue worldwide, affecting the economy of almost every country including India. The use of counterfeit currency is one of the major issues faced throughout the world now-a-days. The counterfeiters are becoming harder to track down because of their use of highly advanced technology. One of the most effective methods to stop counterfeiting can be the use of counterfeit detection software that is easily available and is efficient. Our project will recognize Indian currency notes using a real time image obtained from a webcam. The background of our topic is image processing technology and applying it for the purpose of verifying valid currency notes. The software will detects fake currency by extracting features of notes. The success rate of this software can be measured in terms of accuracy and speed. So our aim is to work on those parameters which will be impossible to implement on counterfeit notes so we started working on minutiae parameters which will be enough to differentiate between fake and original notes.
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