Automatic banknote stain detection

Jiho Yoon; Sangwook Baek; Euisun Choi; Hyunji Jo; Chulhee Lee

doi:10.2352/ISSN.2470-1173.2018.13.IPAS-307

Automatic banknote stain detection

Jiho Yoon, Sangwook Baek, Euisun Choi, Hyunji Jo, Chulhee Lee

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this paper, we propose an automatic banknote stain detection method based on brightness ratio analysis. The method uses median filtering, edge detection and connected component analysis. A median filter was used to eliminate small differences such as serial numbers. The brightness difference between a reference banknote and a target banknote was normalized by using the average brightness and the maximum brightness ratio. Sobel edge detection was used to remove differences created by slight mismatches in the edge areas. After applying a thresholding operation to the difference image, connected component analysis was used to remove spurious stain areas.

Original language	English
Article number	307
Journal	IS and T International Symposium on Electronic Imaging Science and Technology
DOIs	https://doi.org/10.2352/ISSN.2470-1173.2018.13.IPAS-307
Publication status	Published - 2018
Event	16th Image Processing: Algorithms and Systems Symposium 2018 - Burlingame, United States Duration: 2018 Jan 28 → 2018 Feb 1

Bibliographical note

Publisher Copyright:
© 2018 Society for Imaging Science and Technology.

All Science Journal Classification (ASJC) codes

Computer Graphics and Computer-Aided Design
Computer Science Applications
Human-Computer Interaction
Software
Electrical and Electronic Engineering
Atomic and Molecular Physics, and Optics

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10.2352/ISSN.2470-1173.2018.13.IPAS-307

Cite this

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title = "Automatic banknote stain detection",

abstract = "In this paper, we propose an automatic banknote stain detection method based on brightness ratio analysis. The method uses median filtering, edge detection and connected component analysis. A median filter was used to eliminate small differences such as serial numbers. The brightness difference between a reference banknote and a target banknote was normalized by using the average brightness and the maximum brightness ratio. Sobel edge detection was used to remove differences created by slight mismatches in the edge areas. After applying a thresholding operation to the difference image, connected component analysis was used to remove spurious stain areas.",

author = "Jiho Yoon and Sangwook Baek and Euisun Choi and Hyunji Jo and Chulhee Lee",

note = "Publisher Copyright: {\textcopyright} 2018 Society for Imaging Science and Technology.; 16th Image Processing: Algorithms and Systems Symposium 2018 ; Conference date: 28-01-2018 Through 01-02-2018",

year = "2018",

doi = "10.2352/ISSN.2470-1173.2018.13.IPAS-307",

language = "English",

journal = "IS and T International Symposium on Electronic Imaging Science and Technology",

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TY - JOUR

T1 - Automatic banknote stain detection

AU - Yoon, Jiho

AU - Baek, Sangwook

AU - Choi, Euisun

AU - Jo, Hyunji

AU - Lee, Chulhee

PY - 2018

Y1 - 2018

N2 - In this paper, we propose an automatic banknote stain detection method based on brightness ratio analysis. The method uses median filtering, edge detection and connected component analysis. A median filter was used to eliminate small differences such as serial numbers. The brightness difference between a reference banknote and a target banknote was normalized by using the average brightness and the maximum brightness ratio. Sobel edge detection was used to remove differences created by slight mismatches in the edge areas. After applying a thresholding operation to the difference image, connected component analysis was used to remove spurious stain areas.

AB - In this paper, we propose an automatic banknote stain detection method based on brightness ratio analysis. The method uses median filtering, edge detection and connected component analysis. A median filter was used to eliminate small differences such as serial numbers. The brightness difference between a reference banknote and a target banknote was normalized by using the average brightness and the maximum brightness ratio. Sobel edge detection was used to remove differences created by slight mismatches in the edge areas. After applying a thresholding operation to the difference image, connected component analysis was used to remove spurious stain areas.

UR - http://www.scopus.com/inward/record.url?scp=85052881391&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052881391&partnerID=8YFLogxK

U2 - 10.2352/ISSN.2470-1173.2018.13.IPAS-307

DO - 10.2352/ISSN.2470-1173.2018.13.IPAS-307

M3 - Conference article

AN - SCOPUS:85052881391

JO - IS and T International Symposium on Electronic Imaging Science and Technology

JF - IS and T International Symposium on Electronic Imaging Science and Technology

SN - 2470-1173

M1 - 307

T2 - 16th Image Processing: Algorithms and Systems Symposium 2018

Y2 - 28 January 2018 through 1 February 2018

ER -

Automatic banknote stain detection

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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