Currency Note Verification and Denomination Recognition on Indian Currency System
Kaza Deepthi Sudha1, Pooja Kilaru2, Manna Sheela Rani Chetty3
1Kaza Deepthi Sudha, B.Tech Final Year, Department of Computer Science and Engineering, KLEF, Vaddeswaram, Guntur (Andhra Pradesh), India.
2Pooja Kilaru, B.Tech Final Year, Department of Computer Science and Engineering, KLEF, Vaddeswaram, Guntur (Andhra Pradesh), India.
3Manna Sheela Rani Chetty, Professor, Department of Computer Science and Engineering, KLEF, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 23 April 2019 | Revised Manuscript received on 05 May 2019 | Manuscript Published on 17 May 2019 | PP: 184-188 | Volume-7 Issue-6S4 April 2019 | Retrieval Number: F10350476S419/2019©BEIESP
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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: Generally Automatic currency note recognition system is a very useful and important utility in many of the places like banking systems Post offices etc,. Fake currency notes in India with many denominations such as Rs.10, 50, 100, 500 and 2000 are being overwhelmed in the process. In this course of recent years, consequences of the incredible innovative advances in shading printing, copying, and filtering, forging issues have turned out to be increasingly genuine. Here, recognition of notes using the assistance of advanced digital image processing techniques is explained. Two Attributes of Indian paper currency note is chosen for fake detection included ID mark and currency note serial number. The identification mark will help identify the currency note denomination is performed. The feature extraction on the currency note images and then compared with characteristics of non-duplicate currency note. Characteristic extraction is done using canny operator with gradient magnitude. The currency notes are examined by using digital image processing techniques. This methodology consists of a number of steps which includes image processing, edge detection, characteristic extraction, image segmentation, comparing images.
Keywords: Automatic Currency Note Recognition System, Denominations, Advanced Digital Image, Processing Techniques, and Fake Detection.
Scope of the Article: Pattern Recognition