WO2017204519A3 - Vision inspection method using data balancing-based learning, and vision inspection apparatus using data balancing-based learning utilizing vision inspection method - Google Patents

Vision inspection method using data balancing-based learning, and vision inspection apparatus using data balancing-based learning utilizing vision inspection method Download PDF

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Publication number
WO2017204519A3
WO2017204519A3 PCT/KR2017/005326 KR2017005326W WO2017204519A3 WO 2017204519 A3 WO2017204519 A3 WO 2017204519A3 KR 2017005326 W KR2017005326 W KR 2017005326W WO 2017204519 A3 WO2017204519 A3 WO 2017204519A3
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WO
WIPO (PCT)
Prior art keywords
data
vision inspection
inspection method
based learning
inspected
Prior art date
Application number
PCT/KR2017/005326
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French (fr)
Korean (ko)
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WO2017204519A2 (en
Inventor
오병준
전동철
신원종
Original Assignee
(주)에이앤아이
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Publication date
Application filed by (주)에이앤아이 filed Critical (주)에이앤아이
Priority to CN201780001010.9A priority Critical patent/CN109462999B/en
Publication of WO2017204519A2 publication Critical patent/WO2017204519A2/en
Publication of WO2017204519A3 publication Critical patent/WO2017204519A3/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8806—Specially adapted optical and illumination features
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/20—Ensemble learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/0008—Industrial image inspection checking presence/absence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8806—Specially adapted optical and illumination features
    • G01N2021/8809—Adjustment for highlighting flaws
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques

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  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Immunology (AREA)
  • Health & Medical Sciences (AREA)
  • Quality & Reliability (AREA)
  • Chemical & Material Sciences (AREA)
  • Software Systems (AREA)
  • Signal Processing (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Image Analysis (AREA)
  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)

Abstract

A vision inspection method using data balancing-based learning according to the present invention comprises: a prior learning step for establishing a classification criterion, which is the boundary for locations of true and false data, by collecting, mathematizing, and schematizing, in a particular space, images of true samples that are samples of genuinely defective products and false samples that are samples of falsely defective products; a defect determination step for determining the object under inspection as genuinely defective or falsely defective by introducing, into the particular space, data to be inspected, which has been extracted as an image from an object under inspection and mathematized, and determining the area in which the data to be inspected is located in the particular space with the classification criterion as the boundary; and an additional learning step for modifying the classification criterion of the particular space by applying the data to be inspected to the prior learning step, wherein the data to be inspected is modified by means of a data balancing step so that the same number of true data and false data are included, and the defect determination step and additional learning step are repeatedly carried out.
PCT/KR2017/005326 2016-05-23 2017-05-23 Vision inspection method using data balancing-based learning, and vision inspection apparatus using data balancing-based learning utilizing vision inspection method WO2017204519A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201780001010.9A CN109462999B (en) 2016-05-23 2017-05-23 Visual inspection method based on learning through data balance and visual inspection device using same

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR10-2016-0062783 2016-05-23
KR1020160062783A KR101782363B1 (en) 2016-05-23 2016-05-23 Vision inspection method based on learning data

Publications (2)

Publication Number Publication Date
WO2017204519A2 WO2017204519A2 (en) 2017-11-30
WO2017204519A3 true WO2017204519A3 (en) 2018-08-09

Family

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PCT/KR2017/005326 WO2017204519A2 (en) 2016-05-23 2017-05-23 Vision inspection method using data balancing-based learning, and vision inspection apparatus using data balancing-based learning utilizing vision inspection method

Country Status (3)

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KR (1) KR101782363B1 (en)
CN (1) CN109462999B (en)
WO (1) WO2017204519A2 (en)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019208754A1 (en) * 2018-04-26 2019-10-31 大王製紙株式会社 Sorting device, sorting method and sorting program, and computer-readable recording medium or storage apparatus
KR20200039047A (en) 2018-10-01 2020-04-16 에스케이씨 주식회사 Method for detecting defect of film and system therefor
KR102209505B1 (en) * 2018-12-13 2021-02-01 재단법인대구경북과학기술원 Artificial inteligence learning methods and apparatus using analysis of data frequency value
KR102223070B1 (en) * 2019-01-23 2021-03-05 한국과학기술원 Method and apparatus for training neural network
CN116484262B (en) * 2023-05-06 2023-12-08 南通大学 Textile equipment fault auxiliary processing method based on text classification

Citations (5)

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JPH0743126A (en) * 1993-08-02 1995-02-10 Nikon Corp Pattern inspection device
JP2002174603A (en) * 2000-12-08 2002-06-21 Olympus Optical Co Ltd Defect classifying method
JP3756507B1 (en) * 2004-09-17 2006-03-15 シャープ株式会社 Image processing algorithm evaluation method and apparatus, image processing algorithm generation method and apparatus, program, and program recording medium
JP2006292615A (en) * 2005-04-13 2006-10-26 Sharp Corp Visual examination apparatus, visual inspection method, program for making computer function as visual inspection apparatus, and recording medium
KR20100068734A (en) * 2008-12-15 2010-06-24 (주)워프비전 Method for verifying defective on printed circuit board

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Publication number Priority date Publication date Assignee Title
WO2001041068A1 (en) * 1999-11-29 2001-06-07 Olympus Optical Co., Ltd. Defect inspecting system
JP4504612B2 (en) * 2002-08-12 2010-07-14 株式会社日立ハイテクノロジーズ Foreign matter inspection method and foreign matter inspection device
DE602005022753D1 (en) * 2004-11-19 2010-09-16 Koninkl Philips Electronics Nv STRATIFICATION PROCEDURE FOR OVERCOMING INCORRECT FALLANTS IN COMPUTER-AIDED LUNG KNOT FALSE POSITIVE REDUCTION
CN101140619A (en) * 2006-09-05 2008-03-12 大日本网目版制造株式会社 Image processing device, data processing device and parameter adjusting method
US9219886B2 (en) * 2012-12-17 2015-12-22 Emerson Electric Co. Method and apparatus for analyzing image data generated during underground boring or inspection activities
KR20150095053A (en) * 2014-02-12 2015-08-20 한화테크윈 주식회사 Validity verification apparatus of product inspection and method thereof

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0743126A (en) * 1993-08-02 1995-02-10 Nikon Corp Pattern inspection device
JP2002174603A (en) * 2000-12-08 2002-06-21 Olympus Optical Co Ltd Defect classifying method
JP3756507B1 (en) * 2004-09-17 2006-03-15 シャープ株式会社 Image processing algorithm evaluation method and apparatus, image processing algorithm generation method and apparatus, program, and program recording medium
JP2006292615A (en) * 2005-04-13 2006-10-26 Sharp Corp Visual examination apparatus, visual inspection method, program for making computer function as visual inspection apparatus, and recording medium
KR20100068734A (en) * 2008-12-15 2010-06-24 (주)워프비전 Method for verifying defective on printed circuit board

Also Published As

Publication number Publication date
CN109462999A (en) 2019-03-12
CN109462999B (en) 2021-05-07
WO2017204519A2 (en) 2017-11-30
KR101782363B1 (en) 2017-09-27

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