Classifications

• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; 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
  • G02—OPTICS
  • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
  • G02B7/00—Mountings, adjusting means, or light-tight connections, for optical elements
  • G02B7/28—Systems for automatic generation of focusing signals
  • G02B7/36—Systems for automatic generation of focusing signals using image sharpness techniques, e.g. image processing techniques for generating autofocus signals
  • G02B7/365—Systems for automatic generation of focusing signals using image sharpness techniques, e.g. image processing techniques for generating autofocus signals by analysis of the spatial frequency components of the image
• • 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
  • G01J2003/466—Coded colour; Recognition of predetermined colour; Determining proximity to predetermined colour
• • 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
  • G01J3/465—Measurement of colour; Colour measuring devices, e.g. colorimeters taking into account the colour perception of the eye; using tristimulus detection
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; 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
  • G06T2207/30108—Industrial image inspection
  • G06T2207/30124—Fabrics; Textile; Paper
• • G—PHYSICS
  • G06—COMPUTING OR CALCULATING; 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
  • G06T2207/30108—Industrial image inspection
  • G06T2207/30144—Printing quality

Definitions

• the present invention relates to a method for metrological
• radiometric means by color histograms formed in a suitably chosen color space and / or the characteristic values derived therefrom, such as mean values, nounces and similar descriptions known to the person skilled in the art of color textures.
• the present invention further relates to an arrangement for metrological
• Detecting the differences in the visually perceived color impression between a multi-colored patterned surface of a reference and a multicolored patterned surface of a specimen with a light source of substantially constant intensity and spectral distribution to illuminate the multi-colored patterned surface of the specimen, with a spatially resolving sensor for detecting the illuminated surface, and with a computing unit, in which from the signals of the spatially resolving sensor metrological Values describing the color properties of the multicolor patterned surface are determined.
• the image sharpness can be determined by measurement techniques by various methods, such. :
• the image sharpness of the pattern is determined that the values for the characteristics describing the color properties of the specimen with the corresponding predetermined values of the reference and the image definition determining values of the specimen are compared with the corresponding predetermined values of the reference, and that these deviations to the metrological Assessment of visually discernible differences in the color impression are displayed as separate deviation measures.
• the deviation measures become a common deviation measure corresponding to the visual color impression combined and displayed.
• the combination of the color characteristics detecting measurements with the measurements of the image sharpness is preferably done by a parametrisierbare mathematical function, preferably by a polynomial whose parameters were determined experimentally.
• the image sharpness is determined from the brightness of the signals. Since the patterned surface is detected spatially resolved, the light-dark transitions in the local image can be determined on the basis of the brightness signals. The sharper the image, the steeper these transitions,
• the present invention further provides an arrangement by which the visually perceivable color impression of multicolor patterned originals in or near production can be measured and monitored, regardless of whether the physical causes are a change in color and its statistics or lie in a change in the sharpness of the multi-colored patterned print image.
• FIGS. 1 to 3. In these show:
• FIG. 1 schematically shows in a black / white representation the pattern of a multicolored decorative film for floor laminates imitating a wooden surface
• FIG. 2 shows schematically in a black / white representation a reduction of the sharpness of the pattern of FIG. 1 in a strongly oversubscribed representation, for example caused by an inadequate registration of the individual pressure levels and / or by local distortions of the printed paper in the pressure stage,
• FIG. 3 shows by way of example how a section of the decorative film is spatially resolved by a color camera and at the same time a color statistics is obtained from the image signals of the camera, compared with a reference and the deviation measure is displayed, and a measure of the local image sharpness is obtained from the reconstructed brightness image is compared with a reference and the difference in sharpness describing deviation measure is displayed.
• FIG. 1 shows in a black and white representation of a typical multi-colored wood grain with both a correct color reproduction and a correct image sharpness.
• the Surface 10 with this wood grain corresponds to the multicolor patterned surface of a reference according to the present invention.
• Figure 2 shows in comparison (again in black and white representation) the wood grain of Figure 1 with unchanged colors, but one (here for reasons of clarity) extremely exaggerated image blurring.
• the surface 12 with this grain 12 belongs to a test object.
• changed image sharpness is due in particular to two influencing factors:
• FIG. 3 shows by way of a preferred example the individual method steps according to the present invention and components of the arrangement according to the invention.
• the decorative paper 20 printed from left to right in the direction of the arrow and printed in multicolor with a wood pattern is scanned in a section 22 with an imaging, color-capable sensor 24, such as a color line camera (an arrangement of several adjacent discrete color sensors).
• the printed decorative paper 20 is illuminated by a light source 25 of substantially constant intensity and spectral distribution. From the obtained color signals become continuous in a computing unit 26 with methods known from image processing, statistical descriptions of the multicolor are calculated, for example color histograms, which are compared with the reference histograms stored in a unit 28 in a comparison unit 30. The deviation measures resulting from the comparison of the color histograms from the reference and the sample are displayed on a display 32.
• the light source 25 and the imaging color sensor 24 are combined according to a preferred arrangement in a measuring head 27.
• the measuring head 27 has calibration devices for automatic recalibration of the measuring head 27.
• the measuring head 27 is preferably positioned close to the surface, so that no foreign light distorting the measurement from the environment detects the illuminated surface.
• the geometric distribution of the different color patterns applied to the surface can also be determined on the basis of the signals obtained, for example by local density measures.
• One possible parameter for describing the geometric distribution is the local orientation of the color patterns, or similar geometrical texture features known to those skilled in the art. It can also form features of each belonging to a color monochrome elements of the multicolor pattern and / or shape features of visually distinguishable elements of the multicolor pattern are determined.
• the color signals are converted into brightness signals from which a second arithmetic unit 42 continuously determines a measure of the sharpness of the printed image using methods known from optics and image processing and with the reference values stored in a second unit 44 in a second comparison unit 46 compares.
• the deviation measures which are formed by a comparison of the values of the reference and the test object, are displayed by means of a second display 48.
• the image sharpness can also be determined based on the saturation of the signals.
• the signals of the imaging sensor 24 are then present as saturation signals or are converted in the conversion unit 40, from which the arithmetic unit 42 continuously determines a measure of the sharpness of the printed image with methods known from optics and image processing and then compares them with the stored reference values ,
• the color deviation measure and the image sharpness deviation measure are combined in such a way that a resulting deviation measure results which corresponds as well as possible to the visual color deviation perception.
• the color deviation measure and the image sharpness deviation measure are combined by a mathematical function, preferably by a parametrizable mathematical function, preferably by a polynomial whose parameters have been determined experimentally.
• the measured deviation measures are compared with tolerance thresholds. So it is possible by a simple thresholding operation to automatically exclude color vectors that occur too rarely and thus can be considered as interference. But it can also be detected by the tolerance thresholds outliers along the hue axis and excluded from the color control, which are caused for example by the Hereinragen a not belonging to the pattern different colored zone such as a label or a label.
• Laminated decorative paper is to be understood as an example. Basically, for all multicolor patterned surfaces, a change in the visually perceived color impression also depends on the sharpness of the multicolor patterned print.
• the inventive concept is therefore applicable to all multi-colored patterned surfaces where the visual impression must be closely tolerated, regardless of whether they are produced by printing or by other methods and regardless of which materials they consist. It can also be applied to the assessment and comparison of surfaces which are not of a technical nature but of natural origin, such as natural stones, marbles, natural woods, as here too the visual color impression of the statistics of the multicolor and the sharpness of the pattern.
• the invention is not limited to measuring only the color bistograms for physically judging the color deviation besides the image sharpness. It is well known to those skilled in color image processing that other quantities such as the spatial distribution of the pattern portions belonging to the same color and the shape characteristics of the pattern shapes belonging to the same color as well as their statistics influence the visual color perception.
• the essential idea of the invention is that the image sharpness of the pattern is also measured, an intrinsically more geometric property of the image which does not physically depend on these color properties, since they are perceived by the visual system of the human observer not as a geometric property but as a color property becomes.

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• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Computer Vision & Pattern Recognition (AREA)
• General Physics & Mathematics (AREA)
• Optics & Photonics (AREA)
• Quality & Reliability (AREA)
• Theoretical Computer Science (AREA)
• Spectrometry And Color Measurement (AREA)
• Image Processing (AREA)
• Inspection Of Paper Currency And Valuable Securities (AREA)
• Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)

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• 2003
  • 2003-06-24 DE DE10328322A patent/DE10328322A1/de not_active Withdrawn
• 2004
  • 2004-06-21 US US10/562,390 patent/US7596261B2/en not_active Expired - Fee Related
  • 2004-06-21 DE DE112004000051T patent/DE112004000051D2/de not_active Ceased
  • 2004-06-21 DE DE502004005834T patent/DE502004005834D1/de not_active Expired - Lifetime
  • 2004-06-21 WO PCT/EP2004/006695 patent/WO2004113855A1/de not_active Ceased
  • 2004-06-21 ES ES04740130T patent/ES2298770T3/es not_active Expired - Lifetime
  • 2004-06-21 CA CA002528469A patent/CA2528469A1/en not_active Abandoned
  • 2004-06-21 PL PL04740130T patent/PL1642098T3/pl unknown
  • 2004-06-21 AT AT04740130T patent/ATE382853T1/de active
  • 2004-06-21 JP JP2006516013A patent/JP2008533435A/ja active Pending
  • 2004-06-21 EP EP04740130A patent/EP1642098B1/de not_active Expired - Lifetime

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