Indian Counterfeit Currency Detection
Yepuri Spoorthi Hawanika1, Kapavarapu Sai Sreeja2, Yangala Shamitha3, Bandaru Yuva Priyanka4, Manam Srilatha5
1Yepuri Spoorthi Hawanika*, Pursuing, B. tech, Computer Science and Engineering at Velagapudi Ramakrishna Siddhartha Engineering College affiliated to JNTUK, Kakinada.
2Kapavarapu Sai Sreeja, Pursuing Computer Science Program at VR Siddhartha Engineering College affiliated to JNTUK University, Kakinada.
3Yangala Shamitha, Pursuing B. Tech final year in Computer Science and Engineering at VR Siddhartha Engineering College affiliated to JNTUK University, Kakinada.
4Bandaru Yuva Priyanka, Pursuing, B. Tech Computer Science and Engineering at VR Siddhartha Engineering College affiliated to JNTUK University, Kakinada
5Manam Srilatha, Assistant Professor in the Computer Science and Engineering, VR Siddhartha Engineering College, Vijayawada.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on April 10, 2020. | PP: 1746-1749 | Volume-9 Issue-6, April 2020. | Retrieval Number: F4716049620/2020©BEIESP | DOI: 10.35940/ijitee.F4716.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The counterfeit currency printing rate has been increased with the progress of color printing Technology. Some people are printing fake currency using some laser printers. Therefore, the counterfeit currency notes production instead of the original currency notes has been rapidly increasing. This requires an efficient system that identifies the counterfeit currency note and displays the result. This paper developed a system consisting of image preprocessing, gray-scale conversion, image segmentation, edge detection, feature extraction, and comparison modules. The currency note is scanned and the scanned image is used in the modules. The outcome of the system will foretell if the note is counterfeit or genuine.
Keywords: Counterfeit Detection, Gray-Scale conversion, Image Processing, Image Preprocessing, Image Segmentation, Edge Detection, Feature Extraction.
Scope of the Article: Signal and Image Processing