[{“box”:0,”content”:”[if 992 equals=”Open Access”]n
n
Open Access
nn
n
n[/if 992]n
n
n
n
n
n
Liman Harshada, Shikalgar Arbaj, Chavan Aditya, Navnath. S. Govekar,
n
- n t
n
n
n[/foreach]
n
n[if 2099 not_equal=”Yes”]n
- [foreach 286] [if 1175 not_equal=””]n t
- Student, Electronics &Telecommunication,, Student, Electronics &Telecommunication,, Student, Electronics &Telecommunication,, Professor, Electronics &Telecommunication, Rajgad Dnyanpeeth’s Shree Chhatrapati Shivajiraje College of Engineering,, Rajgad Dnyanpeeth’s Shree Chhatrapati Shivajiraje College of Engineering,, Rajgad Dnyanpeeth’s Shree Chhatrapati Shivajiraje College of Engineering,, Rajgad Dnyanpeeth’s Shree Chhatrapati Shivajiraje College of Engineering, Pune, Maharashtra,, Pune, Maharashtra,, Pune, Maharashtra,, Pune, Maharashtra, India, India, India, India
n[/if 1175][/foreach]
n[/if 2099][if 2099 equals=”Yes”][/if 2099]n
Abstract
nFake notes are a global issue. Indian is only one among several. Anyone may now print counterfeit notes thanks to advancements in technology. These notes are created without the state’s legal sanction, and the ongoing production of such notes could hurt a country’s economy. When counterfeit notes are created and distributed, ordinary people cannot identify the difference between real and phony money since they are identifiable by their physical qualities. The most serious issue confronting many countries, including India, is the identification of counterfeit money. Even with automatic machines in banks and other major organizations meant to discern between counterfeit currency notes, ordinary people struggle to do so. Edge detection, feature extraction, image segmentation, acquisition, grayscale conversion, and image comparison are some of the phases in the identification process.
n
Keywords: Machine Learning, CNN, Image Processing, Feature Extraction, Detect Currency, image extraction.
n[if 424 equals=”Regular Issue”][This article belongs to Current Trends in Signal Processing(ctsp)]
n
n
n
n
n
nn[if 992 equals=”Open Access”] Full Text PDF Download[/if 992] n
nn[if 379 not_equal=””]n
Browse Figures
n
n[/if 379]n
References
n[if 1104 equals=””]n
- M. Asha Banu, S. Sandhya, T. V. Sundari and P. R. Shri Ranjani, “Detection of Indian Fake Currency using Image Processing,” 2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2022,pp.695-699, doi: 10.1109/ICAISS55157.2022.10010580..
- Desai, A. Rajadhyaksha, A. Shetty and S. Gharat, “CNN based Counterfeit Indian Currency Recognition Using Generative Adversarial Network,” 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS), Coimbatore, India, 2021, pp. 626-631, doi: 10.1109/ICAIS50930.2021.9395949.
- Bhatia, V. Kedia, A. Shroff, M. Kumar, B. K. Shah and Aryan, “Fake Currency Detection with Machine Learning Algorithm and Image Processing,” 2021 “h International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2021, pp. 755-760, doi: 10.1109/ICICCS51141.2021.9432274.
- M. Colaco, R. Fernandes, Reenaz and S. S, “Efficient Image Processing Technique for Authentication of Indian Paper Currency,” 2021 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2021, pp. 1-8, doi: 10.1109/ICCCI50826.2021.9402428.
- F. Rahman Sarker, M. Israfil Mahmud Raju, A. A. Marouf, R. Hafiz, S. A. Hossain and M. Hossain Khandker Protik, “Real-time Bangladeshi Currency Detection System for Visually Impaired Person,” 2019 International Conference on Bangla Speech and Language Processing (ICBSLP), Sylhet, Bangladesh, 2019, pp. 1-4, doi: 10.1109/ICBSLP47725.2019.201518.
- A. Babu, P. Sridhar and R. R. Vallabhuni, “Fake Currency Recognition System Using Edge Detection,” 2022 Interdisciplinary Research in Technology and Management (IRTM), Kolkata, India, 2022, pp. 1-5, doi: 10.1109/IRTM54583.2022.9791547.
- R. Darade and G. R. Gidveer, “Automatic recognition of fake Indian currency note,” 2016 International Conference on Electrical Power and Energy Systems (ICEPES), Bhopal, India, 2016, pp. 290-294, doi: 10.1109/ICEPES.2016.7915945.
- Shinde, L. Wadhwa, S. Naik, R. Kudale, N. Sherje and K. Mohnani, “Fake Currency Detection using Image Processing,” 2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA), Pune, India, 2023, pp. 1-6, doi: 10.1109/ICCUBEA58933.2023.10392045.
- Patel, R. Nargunde, C. Shah and S. Dholay, “Counterfeit Currency Detection using Deep Learning,” 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kharagpur, India, 2021, pp. 1-5, doi: 10.1109/ICCCNT51525.2021.9579873.
- K. Gautam, “Indian Currency Detection using Image Recognition Technique,” 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), Gunupur, India, 2020, pp. 1-5, doi: 10.1109/ICCSEA49143.2020.913
nn[/if 1104][if 1104 not_equal=””]n
- [foreach 1102]n t
- [if 1106 equals=””], [/if 1106][if 1106 not_equal=””],[/if 1106]
n[/foreach]
n[/if 1104]
nn
nn[if 1114 equals=”Yes”]n
n[/if 1114]
n
n
n
nnn
n
| Volume | 14 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | May 27, 2024 | |
| Accepted | July 19, 2024 | |
| Published | August 20, 2024 |
n
n
n
n
n
n nfunction myFunction2() {nvar x = document.getElementById(“browsefigure”);nif (x.style.display === “block”) {nx.style.display = “none”;n}nelse { x.style.display = “Block”; }n}ndocument.querySelector(“.prevBtn”).addEventListener(“click”, () => {nchangeSlides(-1);n});ndocument.querySelector(“.nextBtn”).addEventListener(“click”, () => {nchangeSlides(1);n});nvar slideIndex = 1;nshowSlides(slideIndex);nfunction changeSlides(n) {nshowSlides((slideIndex += n));n}nfunction currentSlide(n) {nshowSlides((slideIndex = n));n}nfunction showSlides(n) {nvar i;nvar slides = document.getElementsByClassName(“Slide”);nvar dots = document.getElementsByClassName(“Navdot”);nif (n > slides.length) { slideIndex = 1; }nif (n (item.style.display = “none”));nArray.from(dots).forEach(nitem => (item.className = item.className.replace(” selected”, “”))n);nslides[slideIndex – 1].style.display = “block”;ndots[slideIndex – 1].className += ” selected”;n}n”}]