WO2005101312A3 - Fractal skr-method for evaluating image quality - Google Patents

Fractal skr-method for evaluating image quality Download PDF

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Publication number
WO2005101312A3
WO2005101312A3 PCT/EP2005/003889 EP2005003889W WO2005101312A3 WO 2005101312 A3 WO2005101312 A3 WO 2005101312A3 EP 2005003889 W EP2005003889 W EP 2005003889W WO 2005101312 A3 WO2005101312 A3 WO 2005101312A3
Authority
WO
WIPO (PCT)
Prior art keywords
skr
matrix
matrices
rays
image
Prior art date
Application number
PCT/EP2005/003889
Other languages
French (fr)
Other versions
WO2005101312A2 (en
Inventor
Luc Mertens
Original Assignee
Aic
Luc Mertens
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
Application filed by Aic, Luc Mertens filed Critical Aic
Priority to DE602005002739T priority Critical patent/DE602005002739T2/en
Priority to EP05716575A priority patent/EP1735751B1/en
Publication of WO2005101312A2 publication Critical patent/WO2005101312A2/en
Priority to US11/543,623 priority patent/US7953249B2/en
Publication of WO2005101312A3 publication Critical patent/WO2005101312A3/en

Links

Classifications

    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
    • G01J3/462—Computing operations in or between colour spaces; Colour management systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/46—Measurement of colour; Colour measuring devices, e.g. colorimeters
    • G01J3/52—Measurement of colour; Colour measuring devices, e.g. colorimeters using colour charts
    • G01J3/524—Calibration of colorimeters
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection

Abstract

This invention provides an improved method for evaluating the quality of images using a test Skr-matrix system. The index k refers to the fractal level in an Skr-matrix, having matrices themselves as elements. The index r = k refers to the Kronecker sub-level to which a typical internal sum structure is present. Skr-matrices can be explained in terms of cognition numbers, basic components, eigenvalues and sine-like eigenvectors. Skr-matrices also form vector spaces in which matrix distances can be properly calculated. The image Skr-quality parameters are derived from an intermediate quasi-Skr-matrix and its best-Skr-appoximation in relation to a theoretical reference Skr-matrix. Useful applications are in the field of analogue and digital cameras, scanners, vision sensors, monitors, printers, spectrophotometers, infrared cameras, copying machines, TV-screens, GPS screens, X-rays, Gamma rays, Laser rays, or every other component in the image production and image handling field.
PCT/EP2005/003889 2004-04-13 2005-04-13 Fractal skr-method for evaluating image quality WO2005101312A2 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
DE602005002739T DE602005002739T2 (en) 2004-04-13 2005-04-13 FRACTAL SCR METHOD FOR EVALUATING PICTURE QUALITY
EP05716575A EP1735751B1 (en) 2004-04-13 2005-04-13 Fractal skr-method for evaluating image quality
US11/543,623 US7953249B2 (en) 2004-04-13 2006-10-04 Fractal Skr-method for evaluating image quality

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EPPCT/EP2004/003894 2004-04-13
EP2004003894 2004-04-13

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US11/543,623 Continuation US7953249B2 (en) 2004-04-13 2006-10-04 Fractal Skr-method for evaluating image quality

Publications (2)

Publication Number Publication Date
WO2005101312A2 WO2005101312A2 (en) 2005-10-27
WO2005101312A3 true WO2005101312A3 (en) 2006-10-19

Family

ID=34957449

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2005/003889 WO2005101312A2 (en) 2004-04-13 2005-04-13 Fractal skr-method for evaluating image quality

Country Status (4)

Country Link
US (1) US7953249B2 (en)
AT (1) ATE374979T1 (en)
DE (1) DE602005002739T2 (en)
WO (1) WO2005101312A2 (en)

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US7840060B2 (en) * 2006-06-12 2010-11-23 D&S Consultants, Inc. System and method for machine learning using a similarity inverse matrix
US8158928B2 (en) 2008-12-23 2012-04-17 Fluke Corporation System and method for improving the quality of thermal images
US8310548B2 (en) * 2009-10-23 2012-11-13 Contec Llc System and method for video quality parametric tests
DE102010047444B4 (en) * 2010-10-04 2014-04-03 Audi Ag Method for visualizing dimensional deviations between an actual and a target geometry of a component
US8754988B2 (en) * 2010-12-22 2014-06-17 Tektronix, Inc. Blur detection with local sharpness map
US9194800B2 (en) * 2012-10-29 2015-11-24 Tokitae Llc Systems, devices, and methods employing angular-resolved scattering and spectrally resolved measurements for classification of objects
JP6251297B2 (en) * 2013-03-15 2017-12-20 コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． Determination of residual mode image from dual energy image
ES2533778B1 (en) * 2013-09-13 2016-02-02 Abengoa Solar New Technologies S.A. Spectrophotometer for characterization of solar collector receivers
CN104809467B (en) * 2015-04-16 2018-07-06 北京工业大学 A kind of air quality index method of estimation based on dark primary priori
US9836631B1 (en) 2015-04-26 2017-12-05 Aic Innovations Group, Inc. Method and apparatus for fractal identification
KR102387459B1 (en) * 2015-11-20 2022-04-15 삼성전자주식회사 A method for forming pattern of a semiconductor device
US10635909B2 (en) * 2015-12-30 2020-04-28 Texas Instruments Incorporated Vehicle control with efficient iterative triangulation
CN106595512B (en) * 2016-11-09 2017-09-29 华中科技大学 A kind of characterizing method that quantizes of the CNT dispersity based on fractal dimension
JP6969164B2 (en) * 2017-05-31 2021-11-24 株式会社リコー Evaluation device, evaluation program and evaluation method
RU2686257C1 (en) * 2018-04-27 2019-04-24 Ационерное общество "РОТЕК" (АО "РОТЕК") Method and system for remote identification and prediction of development of emerging defects of objects
US10701353B1 (en) 2019-03-20 2020-06-30 United States Of America, As Represented By The Secretary Of The Army Pattern, method, and apparatus for testing imaging system performance
JP2020166492A (en) * 2019-03-29 2020-10-08 コニカミノルタ株式会社 Test apparatus, test method and computer program
CN114782422B (en) * 2022-06-17 2022-10-14 电子科技大学 SVR feature fusion non-reference JPEG image quality evaluation method

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US6024504A (en) * 1997-06-07 2000-02-15 Man Roland Druckmaschinen Ag Process for correcting geometric errors in the transfer of information to a printing stock
US20030044087A1 (en) * 2001-06-12 2003-03-06 Tetsujiro Kondo Apparatus and method for generating coefficient data, apparatus and method for processing information signal using the same, apparatus and method for obtaining coefficient data used therefor, and information providing medium
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US5490516A (en) * 1990-12-14 1996-02-13 Hutson; William H. Method and system to enhance medical signals for real-time analysis and high-resolution display
EP1341384A1 (en) * 1996-08-29 2003-09-03 Fuji Xerox Co., Ltd. Image quality control apparatus and method
US6024504A (en) * 1997-06-07 2000-02-15 Man Roland Druckmaschinen Ag Process for correcting geometric errors in the transfer of information to a printing stock
US20030044087A1 (en) * 2001-06-12 2003-03-06 Tetsujiro Kondo Apparatus and method for generating coefficient data, apparatus and method for processing information signal using the same, apparatus and method for obtaining coefficient data used therefor, and information providing medium
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Also Published As

Publication number Publication date
US7953249B2 (en) 2011-05-31
DE602005002739T2 (en) 2008-07-17
US20070184373A1 (en) 2007-08-09
DE602005002739D1 (en) 2007-11-15
WO2005101312A2 (en) 2005-10-27
ATE374979T1 (en) 2007-10-15

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