Paper Title

A Hybrid Fake Banknote Detection Model using OCR, Face Recognition and Hough Feature

Authors

Prof. Shital S. Aher , Bachhav Prerana Sudam , Gunjal Vaishanvi Ashok , Dhone Vaibhav Shivaji , Yewale Mayur Sakhahari

Keywords

Fake currency, counterfeit detection, image processing, feature extraction

Abstract

In this paper, the programmed framework is intended for ID of Indian cash notes and check whether it is phony or unique. The programmed framework is extremely valuable in banking framework and other field too. In India expansion in the fake money notes of 100, 500 and 1000 rupees. As expansion in the innovation like filtering, variety printing and copying due to that there is expansion in fake issue. In this paper, acknowledgment of phony Indian cash notes is finished by utilizing picture handling method. In this paper, acknowledgment of phony Indian money notes is finished by utilizing picture handling strategy. In this strategy first the picture obtaining is finished and applies preprocessing to the picture. In pre-handling harvest, smooth and change then, at that point, convert the picture into dim variety after change apply the picture division then, at that point, separate elements and diminish, at last looking at picture.

How To Cite

"A Hybrid Fake Banknote Detection Model using OCR, Face Recognition and Hough Feature", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 11, page no.1203 - 1206, November-2022, Available :https://ijsdr.org/papers/IJSDR2211178.pdf

Issue

Volume 7 Issue 11, November-2022

Pages : 1203 - 1206

Other Publication Details

Paper Reg. ID: IJSDR_202856

Published Paper Id: IJSDR2211178

Downloads: 000347215

Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2211178

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2211178

About Publisher

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

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