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WO2012099435A3 - Method for discriminating banknotes using a bayesian approach - Google Patents

Method for discriminating banknotes using a bayesian approach Download PDF

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Publication number
WO2012099435A3
WO2012099435A3 PCT/KR2012/000548 KR2012000548W WO2012099435A3 WO 2012099435 A3 WO2012099435 A3 WO 2012099435A3 KR 2012000548 W KR2012000548 W KR 2012000548W WO 2012099435 A3 WO2012099435 A3 WO 2012099435A3
Authority
WO
WIPO (PCT)
Prior art keywords
banknote
feature vector
discriminating banknotes
present
bayesian approach
Prior art date
Application number
PCT/KR2012/000548
Other languages
French (fr)
Korean (ko)
Other versions
WO2012099435A9 (en
WO2012099435A2 (en
Inventor
최의선
Original Assignee
노틸러스효성 주식회사
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from KR1020110006275A external-priority patent/KR101232683B1/en
Priority claimed from KR1020110006280A external-priority patent/KR101232684B1/en
Application filed by 노틸러스효성 주식회사 filed Critical 노틸러스효성 주식회사
Publication of WO2012099435A2 publication Critical patent/WO2012099435A2/en
Publication of WO2012099435A9 publication Critical patent/WO2012099435A9/en
Publication of WO2012099435A3 publication Critical patent/WO2012099435A3/en

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/84—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using probabilistic graphical models from image or video features, e.g. Markov models or Bayesian networks
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/20—Testing patterns thereon
    • G07D7/202—Testing patterns thereon using pattern matching
    • G07D7/206—Matching template patterns
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/50—Extraction of image or video features by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Multimedia (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • Probability & Statistics with Applications (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Inspection Of Paper Currency And Valuable Securities (AREA)

Abstract

The present invention relates to a method for discriminating banknotes using a Bayesian approach. More particularly, the present invention relates to a method for discriminating banknotes using a Bayesian approach, which comprises dividing a banknote image generated by scanning a banknote into a predetermined number of unit cells, calculating a representative value of each unit cell using sensor data measured in each unit cell, extracting a banknote feature vector which uses the calculated representative value of each unit as a factor, reducing the dimension of the extracted feature vector through a linear feature extraction, and performing banknote discrimination on the feature vector, the dimension of which is reduced, using a Gaussian maximum likelihood (GML) classification. According to the present invention, as compared to conventional methods for discriminating banknotes using a neutral network, banknote class recognition and counterfeit banknote discrimination may be quickly performed, banknote class recognition may be performed relatively accurately, and a counterfeit banknote may be discriminated even from a banknote image having a low resolution.
PCT/KR2012/000548 2011-01-21 2012-01-20 Method for discriminating banknotes using a bayesian approach WO2012099435A2 (en)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
KR10-2011-0006275 2011-01-21
KR10-2011-0006280 2011-01-21
KR1020110006275A KR101232683B1 (en) 2011-01-21 2011-01-21 Method for recognizing denomination of banknotes using Bayesian approach
KR1020110006280A KR101232684B1 (en) 2011-01-21 2011-01-21 Method for detecting counterfeits of banknotes using Bayesian approach

Publications (3)

Publication Number Publication Date
WO2012099435A2 WO2012099435A2 (en) 2012-07-26
WO2012099435A9 WO2012099435A9 (en) 2012-11-01
WO2012099435A3 true WO2012099435A3 (en) 2012-12-20

Family

ID=46516266

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/KR2012/000548 WO2012099435A2 (en) 2011-01-21 2012-01-20 Method for discriminating banknotes using a bayesian approach

Country Status (1)

Country Link
WO (1) WO2012099435A2 (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6858525B2 (en) * 2016-10-07 2021-04-14 グローリー株式会社 Money classification device and money classification method
WO2020003150A2 (en) * 2018-06-28 2020-01-02 3M Innovative Properties Company Image based novelty detection of material samples
GB2586568A (en) * 2019-04-18 2021-03-03 Gerard Rohan Jayamanne Don A technique for detecting counterfeit banknotes, travelers cheques or money orders by a method to be used with smart phone applications (apps)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09171552A (en) * 1995-10-18 1997-06-30 Fuji Xerox Co Ltd Picture recognizing device
US20030192765A1 (en) * 1998-12-02 2003-10-16 Mars Incorporated, A Delaware Corporation Classification method and apparatus
KR100751855B1 (en) * 2006-03-13 2007-08-23 노틸러스효성 주식회사 Recognition method of wavelet using wavelet transform
KR20070093209A (en) * 2006-03-13 2007-09-18 노틸러스효성 주식회사 Recognition method of wavelet using wavelet transform

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09171552A (en) * 1995-10-18 1997-06-30 Fuji Xerox Co Ltd Picture recognizing device
US20030192765A1 (en) * 1998-12-02 2003-10-16 Mars Incorporated, A Delaware Corporation Classification method and apparatus
KR100751855B1 (en) * 2006-03-13 2007-08-23 노틸러스효성 주식회사 Recognition method of wavelet using wavelet transform
KR20070093209A (en) * 2006-03-13 2007-09-18 노틸러스효성 주식회사 Recognition method of wavelet using wavelet transform

Also Published As

Publication number Publication date
WO2012099435A9 (en) 2012-11-01
WO2012099435A2 (en) 2012-07-26

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