EP3882032A1 - Contrôle de feuilles par ajustement global de la luminosité - Google Patents

Contrôle de feuilles par ajustement global de la luminosité Download PDF

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Publication number
EP3882032A1
EP3882032A1 EP20164387.1A EP20164387A EP3882032A1 EP 3882032 A1 EP3882032 A1 EP 3882032A1 EP 20164387 A EP20164387 A EP 20164387A EP 3882032 A1 EP3882032 A1 EP 3882032A1
Authority
EP
European Patent Office
Prior art keywords
image
paper white
print
computer
digital
Prior art date
Legal status (The legal status 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 status listed.)
Granted
Application number
EP20164387.1A
Other languages
German (de)
English (en)
Other versions
EP3882032B1 (fr
Inventor
Bennet Carstensen
Peter Eisele
Jan Krieger
Hendrik Schmedt
Frank Schumann
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Heidelberger Druckmaschinen AG
Original Assignee
Heidelberger Druckmaschinen AG
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.)
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Publication date
Application filed by Heidelberger Druckmaschinen AG filed Critical Heidelberger Druckmaschinen AG
Priority to EP20164387.1A priority Critical patent/EP3882032B1/fr
Priority to CN202110302366.4A priority patent/CN113492580B/zh
Publication of EP3882032A1 publication Critical patent/EP3882032A1/fr
Application granted granted Critical
Publication of EP3882032B1 publication Critical patent/EP3882032B1/fr
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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B41—PRINTING; LINING MACHINES; TYPEWRITERS; STAMPS
    • B41F—PRINTING MACHINES OR PRESSES
    • B41F33/00—Indicating, counting, warning, control or safety devices
    • B41F33/0036—Devices for scanning or checking the printed matter for quality control

Definitions

  • the present invention relates to a method for image inspection of printed products with an automated brightness compensation.
  • the invention lies in the technical field of print quality control.
  • inline means that the image acquisition system, more precisely the camera of the image acquisition system, is mounted in the printing press. It is usually attached after the last printing unit or, if available, a further post-processing station, such as a coating unit, and records the printed products produced by the printing press. It can be a camera or a camera system with several cameras. The use of other image sensors is also possible. For the sake of simplicity, however, the term “camera” is used in the following. The digital print images generated in this way by means of the camera are then compared with corresponding good images of the print subject in an image processing computer.
  • the printed sheets recognized as waste can be ejected via a waste gate. It is extremely important that both the good image reference is error-free and that the real printed image and captured by the image acquisition system really corresponds to the real printed image. Errors caused by the image acquisition, e.g. B. due to a lack of lighting, an unclean lens of the camera or other sources of influence must not have a negative impact on the inspection process.
  • This object is achieved by a method for inspecting images of printed products in a machine processing printing materials by means of a computer, with the printed products produced being recorded and digitized by means of at least one image sensor as part of the image inspection by an image acquisition system, and the resulting recorded digital print images by the computer be compared with a digital reference image and, in the event of discrepancies between the recorded digital print images and the digital reference image, the incorrectly recognized print products are ejected, which is characterized in that the computer separates areas with paper white for print and reference images and determines their color values and displays them Based on the differences between these two color values, it compensates for differences in brightness between print and reference images. With color values, the color value of the respective paper white is meant here.
  • Paper white is already known from prepress, since the print substrate to be used is part of the print job data. By determining a corresponding value for the real paper white of the printed image and comparing it with the nominal value, a corresponding difference in brightness can be determined and compensated for.
  • the target value for the paper white corresponds logically to the paper white of the reference image with which the captured print image is compared in the course of the image inspection. This target value is therefore identical to the paper white known from prepress, since the reference image was either created as a good image from the prepress data.
  • the good image can also be taught in from actually printed print images, with only print images generated without printing errors and with paper white that is as real as possible being used during the teaching process. In this case, the paper white of the reference image may differ slightly from the paper white of the prepress data.
  • a preferred development of the method according to the invention is that the brightness of the print or the reference image is adapted to compensate for the differences in brightness between the print and reference images. It is of secondary importance whether the brightness of the print or the reference image is adjusted, as long as the difference in brightness is balanced out before the two images are compared.
  • a decision criterion could e.g. B. be that you always brighten the darker image or vice versa darken the lighter image. Or you can simplify the algorithm by specifying a corresponding image, print or reference image as the image to be adapted from the outset.
  • the computer checks the standard deviation in paper white in the captured print image in order to exclude paint splashes in the paper white from changing the color value of the paper white in an inadmissible manner.
  • Splashes of paint would falsify the determined color value of the respective area with paper white and thus lead to an incorrect brightness value, which in turn negatively influences the method according to the invention with regard to the adaptation of the brightness difference or even makes it completely unusable. It must therefore be ruled out that there are splashes of paint in the paper white, and this is done by checking the standard deviation in the paper white in the print image accordingly.
  • the computer determines the color value of the paper white by calculating the mean value or the median of all separated paper white areas.
  • the easiest way to proceed is by simply calculating the mean value of the color values of all separated paper white areas and for each of the captured digitized print images and the Compare the reference or good image with one another.
  • Other calculation approaches for the paper white are also conceivable, such as B. to always adopt the darkest or the lightest value in the separated paper white area.
  • Another preferred development of the method according to the invention is that the comparison of the captured digital print images with a digital reference image takes place by the computer for image inspection by creating and evaluating a difference image between the respective captured digital print image and the digital reference image.
  • Several approaches are possible for comparing the captured print images with the digital reference / good image.
  • procedures such as B. the adjustment of pixel to pixel are relatively laborious and expensive
  • the method by means of the formation of a difference image is preferred. In the ideal case, when both images are identical, this difference image is just black, i.e. the color values are zero.
  • the difference image also has the advantage that it can be formed relatively easily from the captured print image and reference image by means of a matrix operation.
  • a further preferred development of the method according to the invention is that the separation of the paper white is carried out by the computer using a threshold value method, with all areas in the image that are darker than the paper white being masked out. After this operation, you only have color values in the corresponding image in areas that correspond to the paper white or are lighter. All other areas are black or have the color value zero.
  • a further preferred development of the method according to the invention is that a predetermined paper white value from the prepress stage is used as the threshold value for the paper white.
  • a predefined value which usually comes from the prepress stage or the reference / good image, must be available. If the reference image is created from the prepress data, this predetermined value should logically be identical to the mean or median value from the reference image. Just in case you want to be sure, too To capture all paper white areas and a blurring in the area assignment is acceptable, the predetermined threshold value can also be lower than the expected paper white value. In the case of creation by teaching-in, the specified value should at least be similar.
  • the threshold value method is applied to the digital reference image, creating a digital mask with which the paper white areas of the respective captured digital print image are separated.
  • the threshold value method is applied to the digital reference image and an image is then obtained in which only the paper white areas have color values above zero, while the rest is correspondingly zero. If this image, which corresponds to a bit mask or a digital mask, is placed over the captured digital print image or multiplied by it, all areas of the print image that are not in the paper white area are masked out in the captured digital print image or to zero set.
  • the separation of the paper white and its color values are determined by the computer by declaring a predetermined area of the printed product to be inspected as the paper white area, in which the color values of the paper white are then determined. If, for whatever reason, the process of separating the paper white areas using a threshold value and a mask generated in this way from the reference image is not possible or too costly, the reference or good image can also simply be analyzed in prepress and the area can thus be determined directly from the print image data and can be used for the method according to the invention. It is even easier if the paper white range is known even without analysis. For example, if there is an area in the existing print image data of the print job which in any case always remains unprinted, e.g. B. on the edge of the print substrate. This fixed and clearly delimited area can then be used to determine the respective paper white value.
  • Another preferred development of the method according to the invention is that before the separation of the paper white for the captured digital print images, these are digitally rectified by the computer.
  • Several algorithms are known from the prior art with which distortions or deformations of the captured digital print image can be compensated for. The additional use of these algorithms naturally facilitates the method according to the invention, since not all deformations of the arch can be covered, recognized and treated by means of the brightness compensation. Furthermore, these algorithms or methods for correcting the print image can usually not completely correct the distortion, so that the method according to the invention is even more efficient in combination with these known methods.
  • Figure 1 shows an example of an image acquisition system 2 which uses the method according to the invention. It consists of at least one image sensor 5, usually a camera 5, which is integrated into the sheet-fed printing press 4. The at least one camera 5 records the print images generated by the printing press 4 and sends the data to a computer 3, 6 for evaluation.
  • This computer 3, 6 can be its own separate computer 6, for example one or more specialized image processing computers 6, or it can also be identical to the control computer 3 of the printing press 4.
  • At least the control computer 3 of the printing press 4 has a display 7 on which the results of the image inspection are displayed.
  • the method according to the invention itself is shown schematically with regard to its sequence in Figure 1 shown in a preferred embodiment.
  • a reference image from prepress and a printed image recorded by a camera are compared with one another by the computer.
  • the method presented here provides for the brightness of the entire sheet to be adjusted in such a way that it optimally fits the reference image and the camera image.
  • an average value for brightness is formed over all paper white areas of the recorded sheet and the reference image. If the two mean values deviate from one another, the brightness of the reference image should be changed in such a way that the mean value of the paper white areas is the same.
  • An important point is the reliable identification of paper white areas.
  • all printed areas in the reference image are identified using a threshold value method. All areas in the image that are darker than paper white do not belong to paper white. In this way, a mask is created which, after rectifying the camera image, is also placed over the camera image. The areas that remain are then consequently paper white.
  • Air turbulence and other effects can cause small sheet deformations on the printing cylinder of the printing machine during image acquisition. These deformations make themselves through both geometric distortions and through Fluctuations in brightness noticeable, as exemplified in Figure 2 shown in the oval darkening in the center of the picture.
  • the aim of the new method is to adjust the global brightness values of the reference image and the camera image in order to avoid pseudo errors due to small arc deformations.
  • the paper white values in the reference image and in the camera image must be determined and then the brightness values must be adjusted.
  • the paper white of the reference image is always set to a defined value in prepress.
  • the paper white mean value in the reference image is 243.
  • All values ⁇ 243 form the subject and can be removed from the reference image using a threshold value method.
  • the resulting image shows in the form of a digital mask Figure 6 .
  • a mean value of the gray values of all pixels in the masked camera image whose gray value is not equal to 0 is now formed.
  • the value for this example image is 226.8.
  • the mean values in paper white between the reference image and the camera image therefore deviate by approx. 13 gray values.
  • the camera image is now brightened by these 13 gray values in order to adapt it to the Adjust reference image. This results in an adapted camera image, which is converted into Figure 8 will be shown.

Landscapes

  • Engineering & Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Inking, Control Or Cleaning Of Printing Machines (AREA)
  • Image Processing (AREA)
EP20164387.1A 2020-03-20 2020-03-20 Contrôle de feuilles par ajustement global de la luminosité Active EP3882032B1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP20164387.1A EP3882032B1 (fr) 2020-03-20 2020-03-20 Contrôle de feuilles par ajustement global de la luminosité
CN202110302366.4A CN113492580B (zh) 2020-03-20 2021-03-22 采用全局亮度适配方式的页张检查方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP20164387.1A EP3882032B1 (fr) 2020-03-20 2020-03-20 Contrôle de feuilles par ajustement global de la luminosité

Publications (2)

Publication Number Publication Date
EP3882032A1 true EP3882032A1 (fr) 2021-09-22
EP3882032B1 EP3882032B1 (fr) 2022-03-30

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
EP20164387.1A Active EP3882032B1 (fr) 2020-03-20 2020-03-20 Contrôle de feuilles par ajustement global de la luminosité

Country Status (2)

Country Link
EP (1) EP3882032B1 (fr)
CN (1) CN113492580B (fr)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102004021601A1 (de) * 2004-05-03 2005-12-01 Gretag-Macbeth Ag Inlinemessung und Regelung bei Druckmaschinen
DE102010031533A1 (de) * 2010-07-19 2012-01-19 Tobias Huneke Verfahren sowie Kontrollfeldanordnung zur Überprüfung der Druckresultate eines Druckers
DE102016224307A1 (de) * 2015-12-15 2017-06-22 Heidelberger Druckmaschinen Ag Verfahren zur Überprüfung eines Bildinspektionssystems
DE102018201794B3 (de) 2018-02-06 2019-04-11 Heidelberger Druckmaschinen Ag Adaptive Bildglättung

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003270164A (ja) * 2002-03-19 2003-09-25 Dainippon Printing Co Ltd 印刷物色調監視装置
DE102007052785A1 (de) * 2007-11-06 2009-05-07 Manroland Ag Verfahren zum Messen der Farbgebung eines bedruckten Bedruckstoffs innerhalb einer Druckmaschine
JP2018054462A (ja) * 2016-09-29 2018-04-05 セイコーエプソン株式会社 測定装置、及び測定方法
JP6797716B2 (ja) * 2017-02-28 2020-12-09 キヤノン株式会社 画像処理装置および画像処理方法
CN110293753B (zh) * 2018-03-22 2021-07-23 海德堡印刷机械股份公司 借助计算机对印刷产品进行图像检测的方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102004021601A1 (de) * 2004-05-03 2005-12-01 Gretag-Macbeth Ag Inlinemessung und Regelung bei Druckmaschinen
DE102010031533A1 (de) * 2010-07-19 2012-01-19 Tobias Huneke Verfahren sowie Kontrollfeldanordnung zur Überprüfung der Druckresultate eines Druckers
DE102016224307A1 (de) * 2015-12-15 2017-06-22 Heidelberger Druckmaschinen Ag Verfahren zur Überprüfung eines Bildinspektionssystems
DE102018201794B3 (de) 2018-02-06 2019-04-11 Heidelberger Druckmaschinen Ag Adaptive Bildglättung

Also Published As

Publication number Publication date
CN113492580A (zh) 2021-10-12
EP3882032B1 (fr) 2022-03-30
CN113492580B (zh) 2023-01-24

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