EP1291179A2 - Test means and method for controlling offset and digital printing - Google Patents

Abstract

Test target for determination of technical print parameters comprises a number of point clusters, that are formed from a number of adjacent image points and are printed as an identifiable print pattern on a print specimen. An Independent claim is made for a method for determining technical print parameters in which the test target is automatically recognized, measured and the required technical print parameters are calculated.

Description

introduction

Conventional print control strips are usually for densitometric or designed for visual exams. Print control strips are divided into test elements, which make it possible to check the individual functions of the printing process. This results in Control strips of considerable size, typically 12mm x 150mm. This kind of Control strip is not generally applicable for process controls, especially when it is on Space for positioning is missing. The use of conventional control agents is equally limited, if the cutting away after printing is not possible and thus the control agent interferes with the observer.

• Messungen im Bild
• Miniaturisierung des Kontrollstreifens

In principle, there are two promising methods to deal with this problem:

• Measurements in the picture
• Miniaturization of the control strip

Measurements in the picture that relate to the original image data will be preferably used for quality assessment of the printing result. In contrast Test element based controls provide information about the Printing process. An overview of the current state of the art can be found in the IFRA report reproduced (Ifra, 2001).

The MiniTarget measuring system described by Künzli et al pursues the second method (Künzli, 1998). It represents a big step in the direction of miniaturization of quality control devices. With its dimensions of 7mm x 10mm, it is possible to capture the entire image information of the MiniTarget by single measurement with a CCD camera and derive the printing parameters mathematically. In the essential characteristics, the MiniTarget concept is understood as a continuation of an idea that is already used in conventional print control strips. In particular, it is analogous to how print control strips are constructed on test elements which are arranged on a small area. With the existing dimensions, the MiniTarget still appears disturbing to the reader. In order to be invisible, or more appropriately "imperceptible", a size is required which is significantly less than 1mm ² .

invention

This fact requires a further miniaturization of the test target in one To the extent that this is perceived at least not obvious. This is a new one methodical approach required.

• Mustererkennung: Schafft die Voraussetzungen für die Ermittlung von Punktcluster Positionen und für die Adaption der Messblende an das Punktmuster der Messprobe
• Charakterisierung von Punktclustern: Damit ist es möglich, die drucktechnischen Parameter aus Punktclustern anstatt aus Rastertonflächen abzuleiten

The image analysis has been used in particular for integral area measurements of grids. However, this application does not exhaust the potential of image analysis for quality and process control. Spatial image analysis combined with sophisticated data analysis are the key to two processes that are fundamentally different from integral measurement techniques such as densitometry and spectrophotometry:

• Pattern recognition: Creates the prerequisites for the determination of point cluster positions and for the adaptation of the measuring orifice to the dot pattern of the test sample
• Characterization of point clusters: This makes it possible to derive the printing parameters from point clusters instead of raster tone areas

There was a new test equipment and method for the determination of printing parameters developed. The invention relates to a pattern of recording dots, such as lines and Surfaces with polygonal or circular boundaries, which is reduced so that it as Part of the printed image for the observer is not or almost not visible.

This test target is magnified microscopically and preferably via CCD camera detected. The signal to noise ratio of the measurement is advantageously increased, which by averaging over several consecutive print patterns. through sophisticated image analysis, it is possible to directly print out the printing parameters to determine the miniaturized patterns. The measures for the reduction of the Test targets are described. Then, by way of example, the application to the type outlined a process control, which is essentially exemplary of the geometric features of a particular dot pattern.

The dot pattern or test target is so small that it is virtually imperceptible to the naked eye by the observer. The dot pattern is formed by a plurality of dot clusters in a typical arrangement, preferably without point closure of the dot clusters with each other. The arrangement of the point clusters is typical in the sense that the dot pattern is identifiable as such in the print copy. The arrangement of the point clusters in the test target, ie the dot pattern, is preferably periodic. The test target has a total area, ie area of the point clusters + area of the spaces, of at most one square millimeter and is preferably square. Preferably, its area is less than 0.5 mm ² . The size specifications with respect to the area advantageously also apply if a virtual frame is drawn around the entirety of the point clusters of the test target, ie the size specification applies to the area within the frame. Each of the dot clusters is preferably printed in exactly one printing ink and is preferably formed from at least two recording dots in the X direction and two recording dots in the Y direction, ie, preferably at least four recording dots immediately adjacent in the X and Y directions. In rotary printing, the X and Y directions correspond to the circumferential and lateral directions. In terms of the greatest possible miniaturization, the printed pixel can advantageously be understood as a recording point.

By means of a sophisticated image analysis can be advantageously from the TestTarget both the density, the color location and the area coverage of each of the individual colors of the Point clusters, as well as being determined in multicolor printing of the passer. In addition, will also allows a reliable diagnosis in terms of pushing and doubling. in the Multicolor printing can use the dot pattern over this also to control the gray balance be used.

The point clusters are at least so large that they can be analyzed planimetrically. The Evaluation is advantageously carried out in the printing press during printing.

For determining color densities and color locations in the overprinting of several Colors, the TestTarget (Dot Pattern) according to the invention with a complementary TestTarget (Trapping Pattern). The supplementary target preferably the same size and shape as the dot pattern based TestTarget. in the Four-color printing, for example, the supplementary TestTarget, depending on the color order, The following four color patches are included: C / M, C / Y, M / Y and C / M / Y. The Trapping Pattern can either side by side to the Dot Pattern or even independently on the Page of the printed copy.

The invention can be used advantageously in offset printing, in particular in wet offset printing. A particularly preferred field of application is newspaper printing Fed rotary printing presses. An inventive test target can advantageously in the image or on non-image areas, in particular on a side edge, printed copy of the newspaper edition. The biggest advantages offers the invention in multi-color printing, although they also with advantage in monochrome Pressure can be used.

Design of dot patterns

Below is a preferred design of a dot pattern using the example of Four-color printing executed and referring to the above-mentioned aspects explained.

The test target is based on a specific dot pattern as shown in Figure 1.

a) Anordnung der Punktcluster C, M, Y und K

b) Darstellung von a) für p=q=2 im quadratischen Raster

c) Druckbeispiel des Musters gemäß b)

Specifications of the dot pattern in the "invisible TestTarget"

a) Arrangement of the point clusters C, M, Y and K.

b) Representation of a) for p = q = 2 in the square grid

c) Printing example of the sample according to b)

C, M, Y and K in Figure 1a symbolize clusters of recording points in the corresponding colors. n is the total number of point clusters in horizontal or vertical direction. The clusters are preferably equal in number to the x and y directions, i.e. 1x1, 2x2, 3x3, ..., p x p adjacent recording points. The Point size corresponds to the addressability of the output device, which in dpi (dots pro inch). The unprinted space in the TestTarget is q pixels both in the x and y directions.

Figure 1b shows an example of a realization of 1a for the parameters n = 4, p = 2 and q =. 2 The point clusters are written in matrix notation by elements with the indices (i, j) designated.

The dot pattern shown in the case of four-color printing is multi-color printing transferable. The arrangement of the colors is preferably such that the from top left to bottom right diagonal point clusters have the same color and in the top one Line in turn, all primary colors are arranged.

For dot-pattern based test targets, a fictitious framework is preferably used in the Way defines that a cell results in a periodic regularity. This Measure is taken with regard to the evaluation, which is not of the Positioning of the measuring aperture should depend. On this topic is below received.

The control method is characterized by the fact that in Figure 1 at a Example test patterns described both the registration errors as well as the printing parameters can be removed. Here it is specifically mentioned that by means of spatially resolving image analysis evaluation not only pushing, doubling, Area coverage can be determined, but point cluster-based parameters can be determined, which in conventional densitometry or spectrophotometry are not accessible.

The presented type of point clusters is characterized by another noteworthy Property off. The dot patterns correspond to small-area halftone dots, which include characteristic information of the printing process. Small-scale point clusters As shown in Figure 1, process-related deviations of the pressure react significantly more sensitive than halftone dots in conventional control strips or in the MiniTarget. The most important influencing factor is the tone gain, which manifests itself in that points in comparison to the theoretical surface occupancy usually too large be reproduced. The effect is visualized in Figure 1b / c. The tone gain increases the point by a fixed amount, which is not the point diameter depends. As a result, the effect increases in inverse proportion to the dot radius. The Type of dot patterns as shown in Figure 1 will respond as a result in particular sensitive to process fluctuations.

The page length of the test target in Figure 1b is calculated as follows: (1a) side length ( in μm ) = 25400 microns dpi ( n * p + ( n -1 ) q ) The percentage dot area A is (1b) A ( in %) = p 2 ( p + q ) 2 * 100%

Typical values for A are 25% with p = q, 16% with p = 2 and q = 3, 11.1% with p = 2 and q =. 4

For the dot pattern in Figure 1b, the page length at 635 dpi output is 0.56 mm. The area is 0.31 mm2. This is more than a hundred times smaller than that MiniTarget after Künzli, 1998.

A supplementary test target was developed especially for the density and color measurements. This test target preferably has the same size and shape as that on a Dot pattern based target. It is in four quadrants in the case of four-color printing divided, which contain printed swatches. These are in the case of Four color printing, depending on the color order, for example, C / M, C / Y, M / Y, and C / M / Y. The target may be side by side with the dot pattern based target, or else be placed independently. It is specially used to increase the color densities in the Overprint and determine the ink acceptance. This is a procedure applied, which is presented in (Künzli, 2000).

When designing the "Invisible TestTargets" must be based on the choice of parameters in Respect to equation (1a / b). n should be out of consideration for the requirement for one kleinflächigen test target be selected small. On the other hand, make sure that the printed dot clusters are representative of the printing process. In determining p and q is to pay particular attention to the Tonwertzunahme. It should be avoided that touch point clusters of the same color on the sample, since then the image analytical Assessment can no longer be made point cluster specific or at least considerably more difficult. For this reason, a test sample with 16% or 11.1% likes Area coverage instead of 25% area coverage would be beneficial.

Production of the test samples

Four samples were prepared for the investigations. The dot patterns were programmed in the programming language PostScript. The specifications are listed in Table 1. Specifications of the samples at a glance Sample No .: Production substratum Dot pattern No. 1: electrophotographic Coated paper p = 2, q = 2 printer (CMYK, 400 dpi) No. 2: electrophotographic recycled paper p = 1, q = 2 (A = 11.1%) Printer (monochrome, 600 dpi) (see Figure 3) No. 3: Newspaper printing newsprint p = 4, q = 8 (A = 11.1%) (monochrome, 1200 dpi) (see Figure 3) # 4: Computer simulation Dot pattern for evaluation pushing / doubling (see Figure 4)

measuring device

The components of the image analysis system preferably close a 3-CCD camera, a microscope, a frame grabber card and an image analysis software. In the In particular, measurement must be done by correctly adjusting the microscope, the lighting and the camera to be taken to get a stable and high-contrast image becomes. Too high amplification of the measurement signal results in a strong noise of the Image.

To determine color values, the image analysis system can be used instead of one after the Tristimulus camera working, even with one, according to the spectral method working, spectrophotometer.

Also critical is the size of the orifice as well as its positioning on the sample to be measured. If the orifice is set small, only a few Point cluster detected. It must therefore be risked that the sample is not representative is, i. the differently colored point clusters not according to their proportionate Occurrence in the sample to be considered. This results in a systematic Measurement error (Romano, 1999). This is especially great when the ratio of Orifice size and the point cluster period has a low value and between two consecutive integers, e.g. 1.5 is. That's why the captured image section is adapted by software to the fictitious image frame, which represents an integer multiple of a period. This will get parameters which are independent of the measuring aperture setting. Basically, that's enough a single point cluster per ink to characterize the printing process. Out However, for sample preparation and metrology, it is recommended that for the measurement at least four point clusters per ink are provided.

The two test fields presented are suitable despite the extremely small dimensions, to perform color and density measurements. The measurement of the solid density and the Color values of the individual colors are made at point clusters. For the measurements of overprinted colors becomes the color field based supplementary test field used, which is described earlier. This requires that the Measuring ranges are calculated by software. For the measurements is a calibration the 3 chip CCD camera required (Künzli, 2000).

methods

The assessment of the digitized images takes place by means of image analysis (Demant Ch., 1998; Jahn B., 1997). The image analysis is based on the RGB image of the test pattern, which in sufficiently high resolution is shown. The diameter of a point cluster should be be recorded by at least 30 pixels. Most measurements will be for each ink made separately. In this case, the channel becomes one with Color evaluated, which is complementary to the observed ink. The determination Threshold is a basic image analysis process to obtain the point clusters from Paper white to distinguish (Barratte Ch., 1995). In the gray value histogram of the Gray value image, the signals of paper white and the ink are determined. As Threshold will be the arithmetic mean of the modal values of paper white and the Ink taken. Artifacts are eliminated during measurement by: small-area structures outside the point cluster positions are removed by image analysis become.

• Berechnung der Mittelpunkte für alle Punktcluster als arithmetisches Mittel aus den x-und y-Koordinaten der zu den Punktclustern gehörenden Pixel
• Unterteilung des Punktmusters in Punktcluster mit periodischer Regelmässigkeit wie z.B. in Abbildung 1 und anschliessende Berrechnung der Passerabweichungen
• Ermittlung der Parameter der Punktcluster, insbesondere Fläche, Gestalt (elliptisch oder rund), die Gleichmässigkeit des Randes
• Berechnung des Schiebens und Dublierens

A preferred evaluation is as follows:

• Calculation of the centers for all point clusters as an arithmetic mean of the x and y coordinates of the pixels belonging to the point clusters
• Subdivision of the dot pattern into point clusters with periodic regularity such as in Figure 1 and subsequent calculation of the register deviations
• Determination of the parameters of the point clusters, in particular surface, shape (elliptical or round), the uniformity of the edge
• Calculation of pushing and doubling

Averaging the signals

Conventional print control strips are characterized by the fact that the printing parameters with sufficient accuracy from the test elements can be removed. In contrast, miniaturized control agents are subject in this regard, limitations, because the sample area only a low number of point clusters contains. These point clusters are subject to random fluctuations, which pressure and material technical conditions are. To a lesser extent, random variations are the result of optical measuring process ago. By signal averaging these difficulties largely be rectified.

• Bestimmung der Eigenschaften eines individuellen Punktclusters in hoher Genauigkeit
• Bestimmung der mittleren Geometrie von Punktclustern

Averaging over N signals increases the signal to noise ratio by a factor of √ N (Bovik, 2000). In the context of the present study two different species are considered, which have different purposes:

• Determination of the properties of an individual point cluster with high accuracy
• Determination of the average geometry of point clusters

In order to determine the properties of an individual point cluster with high accuracy, the measurement process is repeated with the settings kept constant. It is assumed that the noise components of the signals are distributed in a Gaussian manner (Al Bovik, 2000). The averaging is done according to equation 2a. It turned out that this type of averaging is not relevant because the signal to noise ratio is sufficient.

In the second case, signals from different point clusters are used to calculate the mean geometry S (x, y) of a point cluster (Equation 2b). For this purpose, the light intensities I of N different point clusters are detected from test patterns of the same or successive prints. Then the signals are logarithmized. This takes into account that the optical density correlates with the ink layer thickness. Finally, the images of the N point clusters with a common center are superimposed and divided by N. This results in an image representing the average geometry of point clusters (Figure 2).

The physical meaning of the first averaging process is obvious, whereas the physical meaning of the second averaging process must be commented on. In the real world there exists a mean geometry of one calculated in this way Point cluster not. However, the manifestations contain the mean geometry Printing process specific features, which at the single point cluster due Irregularities of the materials used and the reproduction is not apparent are. In a similar way, process parameters can be determined by statistical treatment of the numerical data of all N point clusters (Table 2). A Correspondence between the parameters measured at the averaged point and the Average values of the parameters measured at the individual point clusters are in the case of Surface, shape, density and color values.

register deviations

For the test target in Figure 1b, the centers of each dot pattern for C, M, Y and K are calculated according to Equation (3a-d). (i, j) denote the center point of the point cluster in matrix notation with respect to Figure 1b. (3a) X-cyan = 0.25 (X-cyan (1,1) + X-cyan (2,2) + X-cyan (3,3) + X-cyan (4,4)) Y-cyan = 0.25 (Y-cyan (1,1) + Y-cyan (2,2) + Y-cyan (3,3) + Y-cyan (4,4)) (3b) X-magenta = 0.25 (X-magenta (1,2) + X-magenta (2,3) + X-magenta (3,4) + X-magenta (4,1)) Y magenta = 0.25 (Y magenta (1.2) + Y magenta (2.3 + Y magenta (3.4) + Y magenta (4.1)) (3c) X-Yellow = 0.25 (X-Yellow (1.3) + X-Yellow (2.4) + X-Yellow (3.1) + X-Yellow (4.2)) Y-Yellow = 0.25 (Y-Yellow (1.3) + Y-Yellow (2.4) + Y-Yellow (3.1) + Y-Yellow (4.2)) (3d) X-Black = 0.25 (X-Black (1.4) + X-Black (2.1) + X-Black (3.2) + X-Black (4.3)) Y-Black = 0.25 (Y-Black (1.4) + Y-Black (2.1) + Y-Black (3.2) + Y-Black (4.3))

Finally, the register deviations DX and DY are calculated according to equation (3e-g), using black as reference. (3e) DX (cyan / black) = X-cyan - X-black DY (cyan / black) = Y-cyan - Y-black (3f) DX (magenta / black) = X-magenta - X-black DY (magenta / black) = Y magenta - Y black (3g) DX (Yellow / Black) = X-Yellow - X-Black DY (Yellow / Black) = Y-Yellow - Y-Black

The absolute values of the register deviations become from the distance masses in the Point cluster patterns of the same colors are obtained, which in dpi units of the output device are defined.

The determination of characteristic quantities of the point clusters

Some parameters can be directly derived from the gray value images of the dot patterns in FIG. 3a determine. In this case, the threshold value method converts the gray value image into a binary one Rendered to separate the point clusters from the paper white.

The percentage area coverage is a determining factor in the printing process. in the Contrary to conventional densitometry, the image-analytical surface measurement is based on the principle of planimetry. First, the areas of the point clusters become individual certainly. Then the dot cluster areas are summed for all colors and divided by the area of the fictitious aperture. The resulting value corresponds to the percentage area coverage.

• Umfang des Punktclusters
• grösster/kleinster Durchmesser des Punktclusters
• Lagewinkel (α)

The following parameters are preferably determined from the geometric areas of the point clusters:

• Scope of the point cluster
• largest / smallest diameter of the point cluster
• Position angle (α)

For the point clusters, further parameters are calculated from the above characteristic values.

The parameter E describes the geometry of the point cluster with respect to an ellipse shape. This parameter is used below to determine push and duplicate.

Depending on the resulting value of E, the point cluster tends to have a circular shape (E = 1), to an ellipse shape (E within 0% and 100%) or to a straight line (E = 0%).

The so-called factor R is a measure of the smoothness of the edge course of point clusters (Haberäcker, 1995), which is a characteristic variable of the printing process. R is the ratio of the point cluster area to the square of the circumference (Figure 5): (5) R = 4π * measured area Scope point clusters 2

Depending on the resulting value of R, the boundary is smooth (R = 1), fringed (R within 0 and 1) or as a fractal (R = 0).

Process parameters with diagnostic function

Pushing and doubling are two typical effects in the printing process, which in one indicate disturbed litigation (Romano F., 1998). Can push through different rotational speeds of the two cylinders are caused and manifests itself in broadened lines across the printing direction. The effect manifests itself visually in vertical lines, which are widened and therefore darker appear.

Duplication is caused by register problems between different printing units of Multicolor printing machines cause and express themselves in that the point is sideways shifted and attenuated appears again. Visually, you can see the effect of that Line fields in one direction appear darker as a result of the broadening. In contrast Duplication can occur in any orientation for pushing.

Both types of deviations are visual or metrological by means of sliding or Duplicate fields determined. Figure 4 shows a computer simulation of the effect.

Using image analysis techniques, both effects can be derived from the dot pattern which has already been used for the measurement of the register and the color.

A presence of pushing is calculated according to equation (4) from the factor E in Connection derived with the position angle of the point clusters. From the statistical Treatment trends are visible. A preferred direction is then proven when the standard deviation of the angle is sufficiently small.

• Transformation des originalen Grauwertbildes mittels Schwellenwertverfahren in ein binäres Bild. Der Schwellenwert wird in der Weise gesetzt, dass eine durch dublieren bedingte Punktverbreiterung eingeschlossen wird. Sodann werden die Koordinaten (x,y)-2 der Mittelpunkte der Punktcluster berechnet
• Transformation des originalen Grauwertbildes mittels Schwellenwertverfahren in ein binäres Bild. Der Schwellenwert wird in der Weise gesetzt, dass eine durch dublieren bedingte Punktverbreiterung nicht eingeschlossen ist. Sodann werden die Koordinaten (x,y)-1 der Mittelpunkte der Punktcluster berechnet

Duplication manifests itself in the histogram of the gray values. This essentially shows two signals originating from the paper white and the printed dot clusters. When doubling, the signal of the point clusters is slightly broadened or even shows a page maximum. The extent of doubling is determined according to the following steps:

• Transformation of the original gray value image into a binary image by means of thresholding. The threshold is set to include doubling point broadening. Then the coordinates (x, y) -2 of the centers of the point clusters are calculated
• Transformation of the original gray value image into a binary image by means of thresholding. The threshold is set so that doubling point broadening is not included. Then, the coordinates (x, y) -1 of the centers of the point clusters are calculated

The doubling effect D results from the difference between the two vectors according to equation 6: (6) D = (x, y) -2 - (x, y) -1

Results and discussion

The methods described in the previous chapter have been experimentally verified. For this purpose, samples 1-4 in Table 1 were used. The test results of Samples 1 and 2 are summarized in Table 2.

Representative image analysis results are shown in Figures 2 and 3. Figure 2 shows a three-dimensional plot of a point cluster before and after the averaging.

Relief representation of a point cluster: printed by electrophotographic (left: 126 μ m × 126 μ m) and in newspaper printing (right: 250μ m × 250μ m). The vertical axis represents gray values.

Relief of average dot clusters: printed electrophotographically (left: sample size 36, 126 μ m x 126μ m) and newsprint (right: sample size 41, 250μ 250μ m · m). The vertical axis represents gray values.

Figure 3 shows grayscale images of dot clusters before and after the threshold process.

Gray value images of four point clusters, printed by electrophotography. (left: 250 μ m × 250μ m) and in newspaper printing (right: 500μ m × 500μ m).

Binary images after thresholding the grayscale images in Figure 3a.

The area coverage of the test sample of sample 1 is 8.7%. The sample size is 36 point clusters. The standard deviation of 0.8% results from random process and material variations, which result in point clusters of different sizes. Orientative measurements show that densitometric area measurements generally give larger values. This is justified by the optical light capture, which is not taken into account in the image analysis. In addition, it has been found that the accuracy of the measurements depends significantly on the lighting as well as the choice of the threshold. It is therefore important to pay particular attention to reproducible measurement conditions. The following parameters refer to geometric point clusters and parameters obtained numerically from the surfaces of the point clusters. The dot circumference is 159 μ m , which is slightly smaller than the specified value of 169 μ m due to the smaller area coverage. The ellipsoid factor E is 87%, from which a roundish geometry is concluded. This finding is confirmed from the averaged structure in Figure 2. This also explains that the angle scatters strongly and thus can not recognize a preferred direction. The mean is 73 degrees and has a standard deviation of 59 degrees. The factor R of 0.72 indicates an uneven edge structure. This finding is visually consistent with the relief representation in Figure 2a and the gray scale images in Figure 3. The results of the newspaper print patterns show a similar behavior as Sample 1.

Density and color measurements can be made equally on the test pattern in Figure 1 be performed. Previously, the image analysis system is calibrated according to a method which is described in the literature (Künzli, 1998). It allows the conversion from RGB values to colorimetric and density values. For the measurements are diaphragms which determines the point clusters selectively.

The averaging of signals was on the electrophotographic (sample 2) and in the newspaper printing (Sample 3) printed sample examined. In Figure 2, the point clusters are present and reproduced after averaging. It is obvious that the averaged Structures have smoother gradients compared to the structures of individual points. The averaged structures in Figure 2 indicate that the electrophotographic point clusters produced tend to a square structure. In contrast to The dot clusters in newspaper printing have a rounded shape. From the comparison of Results in Table 2 show that the calculated from the individual values Parameters of the point clusters agree well with the parameters, which from the averaged structures were determined. This applies to the absolute surfaces that percentage area coverage, the ellipsoid factor E and the largest and smallest Diameter too. In the case of the edge smoothness R, for the averaged structures 0.92 in Newspaper printing and 0.91 for electrophotography obtained. These values are as expected significantly higher compared to the corresponding averages of 0.65 and 0.72 in Table 2. This difference is due to the smoothing effect, which is due to the averaging results.

The registration differences were determined according to equation (3a-g) from the test pattern of the color printer (sample 1). There were obtained deviations which lie between 15 and 55 μ m. This value is below the specified diameter of the dot cluster which amounts to 63 μ m. The values determined lie within the tolerances of offset printing, which are given in ISO 12647-2 as 83.3 μ m for 60 l / cm. Overall, the results show that the analysis of the registration deviations can be made on a test pattern which does not appear conspicuously.

Figure 4 shows the computer simulation of pushing and doubling.

a) Muster von runden Punktclustern

b) Schieben

c) Dublieren

Assessment of pushing and doubling (computer simulation)

a) Pattern of round point clusters

b) pushing

c) duplication

The analysis of the pushing was made on a sample, which by Computer simulation (see Figure 4b). The evaluation is based on the ellipsoid factor E in equation 4. The smallest and largest diameters became too 1.72 and 1.77 relative units, and the angle is 172 degrees. These values agree well with the input values of the computer simulation. This is one Pushing detected quantitatively. The analysis of doubling in Figure 4c is done according to equation 6. The resulting vector difference is called distance and angle calculated with respect to the center point coordinates of the point cluster without duplication. It are obtained a distance of 0.18 relative units and an angle of 145 degrees. Slight variations of these values are attributed to digital noise, which was introduced during modeling.

Conclusions and outlook

The present study shows that the newly developed test pattern or TestTarget can be used in conjunction with the described evaluation methodology for the control of multicolor printing. The process is especially popular where process control is required, but for reasons of space, no control strips can be used. With a test pattern area that is well below 1mm ² , an almost unlimited use is possible. In particular, a targeted positioning can now be made close to selected image locations. With the described method, the limits of what was possible were rigorously explored. They culminate in the statement that the parameters relevant to printing technology can ultimately be taken from a test pattern which is made up of one point cluster per printing ink. However, an averaging over a plurality of successively printed print patterns is advantageous. All of the described measures, which in their entirety allow such a miniaturization of the test target, were tested experimentally or by simulation.

With the application of prediction methods as currently used by EMPA, St. Gallen, Switzerland, is an extrapolation of results across the whole Range of the tone curve promising (Mourad, 2001).

credentials

1. Barratte Ch., Dalphond JE, Mangin PJ and Valade JL, (1995), An Automatic Determination of Threshold for the Image Analysis of Prints. Proceedings of the 23 ^rd Conference of Research IARIGAI, Paris, 451-469

2. Bovik Alan C., (2000), Handbook of Image and Video Processing, Academic Press, new York

3. Demant Ch., Streicher-Abel B. and Waszkewitz P., (1998), Industrielle Image processing, Springer Verlag, Heidelberg

4. Haberäcker P., (1995), Praxis der digital Bildverabeitung. 4th edition, Hanser, Munich

5. Ifra, (2001), Closed loop printing quality control for coldset web offset (to be published), Darmstadt

6. Jähne B., (1997), Digital Image Processing, Springer Verlag, Heidelberg

7. Künzli H., et al, (1998), Mini Targets: A new dimension in print quality control, SPIE Conf. Proc., Vol 3300, pp 286-91

8. Künzli H., (2000), How to Convert RGB Signals to Colorimetric and Densitometric values, Proceedings of SPIE, Vol. 3963, 70-76

9. Künzli H., (2000), MiniTarget for Quality Control in Newspaper Printing, TAGA Proceedings, 509-520

10. Mourad S., et al. (2001), Predicting Transmittance Spectra of Electrophotographic Color Prints, Proceeding of SPIE, Vol. 4300, 50-57

11. Romano D., (1999), Recorder spot size and its effect on image quality and halftone reproduction, 280-293

12. Romano F.J., Romano R.M., (1998), Encyclopedia of graphic communications, GATF, Prentice Hall, London

Claims (14)

TestTarget for determining printing-technical parameters, the multiple point clusters each formed by a plurality of adjacent recording dots and in the form of a dot pattern identifiable as such Printed copies are printed. Test target according to claim 1, characterized in that it contains several point clusters of an ink. TestTarget according to one of the preceding claims, characterized in that it contains at least one individual color point cluster of a plurality of individual colors, preferably of all individual colors of the print. Test target according to one of the preceding claims, characterized in that it is formed solely by the point clusters. TestTarget according to one of the preceding claims, characterized in that none of the point clusters is in point-to-point with an adjacent point cluster of the test target. TestTarget according to one of the preceding claims, characterized in that the point clusters form a dot pattern as a matrix whose rows and columns are fully occupied with the point clusters as matrix elements. Test target according to one of the preceding claims, characterized in that the point clusters form a matrix in whose rows the individual colors of the print are arranged in sequence. Test target according to one of the preceding claims, characterized in that the point clusters form a matrix in whose columns the individual colors of the print are arranged in sequence. Test target according to one of the preceding claims, characterized in that the point clusters are arranged in the form of a matrix whose diagonals are each formed by point clusters of only one single color of the print, each individual color of the print forming at least one diagonal preferably having at least two point clusters. Method for determining printing parameters using the test target according to one of the preceding claims, in which: a) the test target is detected automatically, b) measured c) and to determine the printing parameters, such as area coverage, solid density and / or color value and / or for diagnosis with respect to sliding and / or duplication, is evaluated. Method according to the preceding claim, characterized in that the test target is recognized by image analysis as a test target. Method according to one of the preceding claims, characterized in that the point clusters of the test target are measured planimetrically. Method according to one of the preceding claims, characterized in that diameter, circumference and shape (position angle α, ellipse parameter E, factor R) of the punk clusters are determined. Method according to one of the preceding claims, characterized in that the determined printing parameters for controlling and preferably for controlling and / or regulating the printing process are used in a control and / or regulation.