An Automatic Recognition of Fake Currency Note Using Raspberry Pi

Authors(2) :-M. Sravan Kumar, B. Jyothi Priya

Programmed identification and acknowledgment of Indian money note has picked up a ton of research consideration as of late especially because of its inconceivable potential applications. In this paper we present another acknowledgment technique for Indian money utilizing PC vision. It is demonstrated that Indian monetary standards can be grouped in light of an arrangement of one of a kind non separating components, for example, shading, measurement and above all the Identification Mark (remarkable for every category) specified in RBI rules. Right off the bat the prevailing shading and the perspective proportion of the note are separated. After this the division of the segment of the note containing the exceptional I.D. Check is finished. From these divided picture, include extraction is done utilizing Fourier Descriptors. As each note has a one of a kind shape as the I.D. Check, the arrangement of these shapes is finished with the assistance of Artificial Neural Network. After component extraction, the divisions are perceived in light of the created calculation.

Authors and Affiliations

M. Sravan Kumar
Assistanr Professor, Tadipatri Engineering College, Tadipatri, Anantapur, India
B. Jyothi Priya
Assistanr Professor, Tadipatri Engineering College, Tadipatri, Anantapur, India

Raspberry Pi, RFID framework, MATLAB, HSV, Ultra Violet, IMAQ LABVIEW

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 356-360
Manuscript Number : CSEIT183184
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

M. Sravan Kumar, B. Jyothi Priya, "An Automatic Recognition of Fake Currency Note Using Raspberry Pi", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.356-360, January-February-2018.
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