Printed product inspection system

Abstract

The application provides a printed product detection system for color quality detection of a printed product printed by a printing device, characterized in that the system comprises: an image acquisition device for acquiring an image of the printed product to obtain a corresponding target image, the printed product being a paper printed product printed with a predetermined image and at least one detection color bar; a color value extraction unit for extracting a color value of the detection color bar in the target image as a to-be-detected color value; a detection parameter reconstruction unit for reconstructing a corresponding detection parameter as a reconstructed detection parameter according to the to-be-detected color value; a judgment unit for judging whether the reconstructed detection parameter is consistent with a predetermined target parameter, and when the judgment result is no, a printing control unit adjusts a printing parameter of the printing device according to the reconstructed detection parameter and the predetermined target parameter. The width of the detection color bar is 0.2 mm-2 mm. The printed product detection system can quickly and efficiently reconstruct the detection parameter on the basis of the detection color bar with a relatively narrow width, and is energy-saving and environment-friendly.

Description

Technical Field

[0001] This invention belongs to the field of color measurement technology, specifically relating to a printing product inspection system. Background Technology

[0002] The spectral data of a color is called a color "fingerprint," which is unique. Colors reproduced through spectral analysis remain constant within visual latitude and under most lighting conditions. This ensures that the reproduced colors can be accurately reproduced under various lighting and observation conditions. Spectral reflectance refers to the ratio of the luminous flux reflected by an object to the incident luminous flux. It represents the remaining colored light reflected after the object selectively absorbs the light source. It is unaffected by external factors, and the color characteristics of an object under different light sources can be predicted based on spectral reflectance.

[0003] In fields such as printing color inspection, printing quality control, fabric printing, and art reproduction, the spectral reflectance of color blocks is often used to further obtain quality control parameters such as chromaticity, brightness, saturation, solid density, dot area ratio, and dot gain of the color blocks. These quality control parameters are then used to control the product quality during the production process.

[0004] In existing technologies, the spectral reflectance of color blocks needs to be measured using specialized measuring equipment to calculate quality control parameters. However, this measurement process requires color blocks to be at least 5mm wide for the equipment to detect the corresponding spectral reflectance. Color blocks wider than 5mm not only waste excessive ink but also end up as waste paper during binding, resulting in material waste and environmental inefficiency. Furthermore, the measuring equipment is expensive and complex to operate, and repair costs are high when malfunctions occur. Therefore, this hinders cost reduction in industrial production and large-scale application in the industrial sector. Summary of the Invention

[0005] To address the above problems, this invention provides an environmentally friendly and energy-saving printing product testing system. The invention employs the following technical solution:

[0006] This invention provides a printed product inspection system for color quality inspection of printed products produced by a printing device. The system comprises: an image acquisition device for acquiring an image of the printed product to obtain a target image; the printed product is a paper-based printed product bearing a predetermined image and at least one detection color bar; a color value extraction unit for extracting the color value of the detection color bar in the target image as the color value to be measured; a detection parameter reconstruction unit for reconstructing corresponding detection parameters based on the color value to be measured as reconstructed detection parameters; a judgment unit for judging whether the reconstructed detection parameters match the predetermined target parameters; and a printing control unit for adjusting the printing parameters of the printing device based on the reconstructed detection parameters and the predetermined target parameters when the judgment unit judges against the target parameters, so that the printing device prints a printed product that conforms to the predetermined target parameters. The image acquisition device has at least a guide rail and a scanning head. The guide rail transports the printed product to the scanning head, allowing the scanning head to scan the transported printed product to obtain the target image. The width of the detection color bar is 0.2mm-2mm.

[0007] In the printing product inspection system provided by the present invention, it may also have the following features: wherein the reconstructed detection parameter is spectral reflectance, the predetermined target parameter is standard spectral reflectance, the detection parameter reconstruction unit has a model reconstruction unit, the judgment unit has a spectral reflectance judgment unit, the model reconstruction unit reconstructs the color value to be tested through a pre-trained spectral reconstruction model to obtain the corresponding spectral reflectance, and the spectral reflectance judgment unit judges whether the spectral reflectance matches the standard spectral reflectance.

[0008] In the printed product inspection system provided by this invention, it may also have the following features: the pre-trained spectral reconstruction model has an autoencoder and a detection network; the spectral reflectance includes multiple bands and the intensity value of each band; the autoencoder has an encoder for encoding the spectral reflectance with multiple bands into a predetermined number of encoded data and a corresponding decoder for decoding the encoded data into spectral reflectance; the detection network is pre-trained through the following steps: Step S1-1, acquiring a standard image obtained by the image acquisition device from a standard printing template, the standard image containing multiple standard color blocks; Step S1-2, acquiring the color values ​​of the standard color blocks as standard colors. The standard color values ​​and their corresponding spectral reflectance are used as standard spectral reflectance. Step S1-3: The standard color values ​​are clustered to divide multiple standard color values ​​into several color clusters. Step S1-4: The standard color values ​​in each color cluster are sorted according to their size to form several ordered color clusters. Step S1-5: The standard spectral reflectance corresponding to each standard color value is sequentially input into the encoder to obtain the corresponding encoded data as standard encoded data. Step S1-6: According to the order of the standard color values ​​in each ordered color cluster, the initial detection network is trained sequentially based on the standard color value and the corresponding standard encoded data until the predetermined conditions are met and a trained detection network is obtained.

[0009] The printing product inspection system provided by the present invention may also have the following feature: the spectral reflectance has 31 bands and the predetermined number of categories is 3 to 12.

[0010] The printing product inspection system provided by the present invention may also have the following feature, wherein the predetermined number of categories is 3 or 8.

[0011] In the printing product inspection system provided by the present invention, it may also have the following features: the reconstructed detection parameter is a chromaticity value, the predetermined target parameter is a standard chromaticity value, the detection parameter reconstruction unit has a standard chromaticity value storage unit and a chromaticity value reconstruction unit, the judgment unit has a chromaticity value judgment unit, the standard chromaticity value storage unit stores multiple color values ​​and corresponding chromaticity values, the chromaticity value reconstruction unit retrieves the corresponding chromaticity value from the standard chromaticity value storage unit according to the color value to be measured, and the chromaticity value judgment unit judges whether the chromaticity value matches the standard chromaticity value.

[0012] The printing product inspection system provided by this invention may also have the following feature, wherein the chromaticity value is an XYZ value or a LAB chromaticity value.

[0013] In the printing product inspection system provided by the present invention, the width of the color block to be tested is 0.5 mm or 1 mm.

[0014] In the printing product inspection system provided by the present invention, the image acquisition device may also have the following feature: the image acquisition device has a suction plate with multiple suction holes for adsorbing the printed product, so that the printed product is in close contact with the suction plate.

[0015] The printing product inspection system provided by this invention may also include a prompting unit that generates a prompt indicating that the printing product does not meet the standard when the judgment unit determines that it is not, thereby reminding the operator to take appropriate action on the printing product.

[0016] Invention Function and Effect

[0017] According to the printed product inspection system of the present invention, since the width of the inspection color bar is 0.2mm-2mm, which is much smaller than the 5mm in the prior art, ink is saved. Furthermore, since the inspection color bar is eventually cut off and discarded, the narrower inspection color bar is more energy-efficient and environmentally friendly. Moreover, since the printing control unit can adjust the printing parameters of the printing device based on the reconstructed inspection parameters and the predetermined target parameters, printed products that meet the predetermined target parameters can be obtained, thus improving the quality of the printed products.

[0018] The printing product inspection system of this invention can quickly and efficiently reconstruct inspection parameters based on narrow inspection color bars, while being energy-saving and environmentally friendly. Attached Figure Description

[0019] Figure 1 This is a structural block diagram of the printed product inspection system according to an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of a printed product according to an embodiment of the present invention.

[0021] Figure 3 This is a schematic diagram of the image acquisition device according to an embodiment of the present invention;

[0022] Figure 4 This is a flowchart of the detection network training process according to an embodiment of the present invention;

[0023] Figure 5 The experimental comparison diagrams are for embodiments of the present invention; and

[0024] Figure 6 This is a flowchart illustrating the working process of the printed product inspection system according to an embodiment of the present invention. Detailed Implementation

[0025] To make the technical means, creative features, objectives and effects of the present invention easy to understand, the following describes a printing product inspection system of the present invention in detail with reference to embodiments and accompanying drawings.

[0026] <Example>

[0027] Figure 1 This is a structural block diagram of a printed product inspection system according to an embodiment of the present invention.

[0028] like Figure 1 As shown, a printed product inspection system 1 includes an image acquisition device 11, a color value extraction unit 12, an inspection parameter reconstruction unit 13, a judgment unit 14, a printing control unit 15, and a prompting unit 16.

[0029] The image acquisition device 11 is capable of acquiring images of printed products to obtain corresponding target images. The printed products are paper printed with a predetermined image and at least one detection color bar 102.

[0030] Figure 2 This is a schematic diagram of a printed product according to an embodiment of the present invention.

[0031] like Figure 2 As shown, the printed product 10 includes a printed image area 101 and a detection color bar 102. The detection color bar 102 contains a color bar 1021 composed of color blocks of the same color and a color bar 1022 composed of multiple color blocks of different colors. Each color block to be tested is a rectangular color block. In this embodiment, the width of the rectangular color block is 0.2 mm, and the width of the detection color bar 102 is 1 mm.

[0032] Figure 3 This is a schematic diagram of the image acquisition device according to an embodiment of the present invention.

[0033] like Figure 3 As shown, the image acquisition device 11 has a suction plate 111, a guide rail 112, and a scanning head 113.

[0034] The suction plate 111 has multiple suction holes, which can adsorb printed products and make the printed products stick tightly to the suction plate 111.

[0035] The guide rail 112 transports the printed product to the scanning head 113, enabling the scanning head 113 to scan the transported printed product and obtain the corresponding target image.

[0036] The guide rail 112 can be either a rack and pinion or a lead screw guide rail 112.

[0037] The color value extraction unit 12 can extract the color value of the detection color bar 102 in the target image as the color value to be measured.

[0038] In this embodiment, the color value is an RGB value. The color value extraction unit 2 first determines the pixel point in the scanned image corresponding to each color block to be tested, and then reads the RGB value of the pixel point to use as the color value to be tested for each color block to be tested.

[0039] The detection parameter reconstruction unit 13 can reconstruct the corresponding detection parameters based on the color value to be measured as the reconstructed detection parameters.

[0040] The judgment unit 14 can determine whether the reconstructed detection parameters match the predetermined target parameters.

[0041] When the judgment unit 14 determines that it is true, the image acquisition device 11 acquires the target image corresponding to the next printed product and performs a new detection.

[0042] When the judgment unit 14 determines that the product does not meet the standard, the prompting unit 16 generates a prompt that the printed product does not meet the standard, thereby reminding the operator to take appropriate action on the printed product.

[0043] In this embodiment, the situation where the reconstructed detection parameters do not match the predetermined target parameters is that the color position deviates due to paper offset during the printing process of the printed product, or the color is too light due to insufficient ink concentration, which does not meet the standard.

[0044] In both of the above situations, the prompting unit 16 generates a prompt indicating that the printed product does not meet the standard, and the operator handles the non-compliant printed product properly according to the prompt.

[0045] Next, the printing control unit 15 adjusts the printing parameters of the printing device according to the reconstruction detection parameters and the predetermined target parameters, so that the printing device prints a printed product that meets the predetermined target parameters.

[0046] In this embodiment, the reconstructed detection parameter is spectral reflectance, and the predetermined target parameter is standard spectral reflectance.

[0047] The detection parameter reconstruction unit 13 has a model reconstruction section.

[0048] The judgment unit 14 has a spectral reflectance judgment section.

[0049] The model reconstruction department reconstructs the color value to be measured using a pre-trained spectral reconstruction model, thereby obtaining the corresponding spectral reflectance.

[0050] The pre-trained spectral reconstruction model includes an autoencoder and a detection network.

[0051] Spectral reflectance includes multiple bands and the intensity value of each band.

[0052] In this embodiment, the spectral reflectance has 31 bands.

[0053] The autoencoder has an encoder for encoding spectral reflectance with multiple bands into a predetermined number of coded data and a corresponding decoder for decoding the coded data into spectral reflectance.

[0054] The detection network is a least squares support vector regression model.

[0055] The predetermined quantity categories range from 3 to 12, and in this embodiment, the predetermined quantity categories are 8.

[0056] Figure 4 This is a flowchart of the detection network training process according to an embodiment of the present invention.

[0057] like Figure 4 As shown, the detection network is obtained in advance through the following training steps:

[0058] Step S1-1: Obtain a standard image of the standard printing template by the image acquisition device 11. The standard image contains multiple standard color blocks.

[0059] The standard printing templates can be Munsell color charts, NCS (Natural Colour System) color charts, etc.

[0060] Step S1-2: Obtain the color value of the standard color block as the standard color value and the corresponding spectral reflectance as the standard spectral reflectance.

[0061] In this embodiment, the standard color value is obtained by the color value extraction unit. The specific extraction method is the same as the method used by the color value extraction unit to extract the color value to be measured, and will not be described again here. The standard spectral reflectance is the spectral reflectance obtained by detecting each color patch with a spectrometer.

[0062] Steps S1-3 involve clustering the standard color values ​​to divide multiple standard color values ​​into several color clusters.

[0063] Steps S1-4: Sort the standard color values ​​in each color cluster according to their size to form several corresponding ordered color clusters.

[0064] Step S1-4 further includes the following sub-steps:

[0065] Step S1-4-1: Sort each color cluster sequentially according to the size of its RGB values ​​to form an RGB value sequence;

[0066] Step S1-4-2: Extract a predetermined number of RGB values ​​from the RGB value sequence at predetermined intervals, and form an ordered color cluster from the extracted RGB values.

[0067] Steps S1-5: Input the standard spectral reflectance corresponding to each standard color value into the encoder sequentially to obtain the corresponding encoded data as standard encoded data.

[0068] Steps S1-6: According to the order of the standard color values ​​in each ordered color cluster, the initial detection network is trained sequentially based on the standard color value and the corresponding standard encoding data until the predetermined conditions are met and a trained detection network is obtained.

[0069] To verify the performance of the detection network, the test color values ​​from the training and test datasets were input into the trained detection network to obtain the predicted encoded data corresponding to each test color value. The autoencoder then decoded the data to obtain the predicted value of the spectral reflectance corresponding to the test color value. The evaluation parameters were calculated using the predicted value and the actual value of the spectral reflectance corresponding to each test color value.

[0070] The evaluation parameters include root mean square error, average color difference, maximum color difference, and one or more fitting evaluation factors. The evaluation parameters are compared with preset parameters. If the comparison result between the evaluation parameters and the preset parameters meets the preset conditions, the trained detection network performs well and can be applied in practice. Specific experimental results are shown below. Figure 5 As shown.

[0071] For the training set data, the calculated root mean square error is 0.0065, the average color difference deltaE00 is 0.0799, the maximum color difference deltaE00 is 0.510, and the evaluation factor is 0.9995. For the test set data, the calculated root mean square error is 0.0137, the average color difference deltaE00 is 0.10, the maximum color difference is 1.1, and the fitting evaluation factor is 0.9980. In this application scenario, the maximum allowable color difference deltaE00 is generally set to 2.5, therefore, it can be determined that the trained detection network can be applied to real-world scenarios.

[0072] from Figure 5 It is evident that the spectral reconstruction model provided in this embodiment has higher recognition accuracy compared to traditional spectral reconstruction models.

[0073] The spectral reflectance determination unit determines whether the spectral reflectance matches the standard spectral reflectance.

[0074] The printing control unit 15 adjusts the printing parameters of the printing device based on the spectral reflectance and the standard spectral reflectance.

[0075] Figure 6 This is a flowchart illustrating the working process of the printed product inspection system according to an embodiment of the present invention.

[0076] like Figure 6As shown, the working process of the printed product inspection system includes the following steps:

[0077] Step S2-1: The image acquisition device 11 acquires images of the printed product to obtain the corresponding target image, and then proceeds to step S2-2.

[0078] Step S2-2: The color value extraction unit 12 extracts the color value of the detected color bar 102 in the target image as the color value to be measured, and then proceeds to step S2-3;

[0079] In step S2-3, the model reconstruction unit reconstructs the color value to be measured using a pre-trained spectral reconstruction model to obtain the corresponding spectral reflectance, and then proceeds to step S2-4.

[0080] Step S2-4: The spectral reflectance determination unit determines whether the spectral reflectance matches the standard spectral reflectance. If the determination is negative, proceed to step S2-5; if the determination is positive, proceed to step S2-1 to obtain the target image corresponding to the next printed product.

[0081] In step S2-5, the prompting unit 16 generates a prompt that the printed product does not meet the standard. At the same time, the printing control unit 15 adjusts the printing parameters of the printing device according to the spectral reflectance and the standard spectral reflectance, and then enters the end state.

[0082] Functions and effects of the embodiments

[0083] According to the printed product inspection system provided in this embodiment, the width of the inspection color bar is 0.2mm-2mm, which is much smaller than the 5mm in the prior art, thus saving ink. Furthermore, since the inspection color bar is eventually cut off and discarded, the narrower inspection color bar is more energy-efficient and environmentally friendly. Moreover, because the printing control unit can adjust the printing parameters of the printing device based on the reconstructed detection parameters and predetermined target parameters, printed products that meet the predetermined target parameters can be obtained, improving the quality of the printed products.

[0084] In this embodiment, since the model reconstruction unit reconstructs the spectral reflectance of the color value to be tested using a pre-trained spectral reconstruction model, the accuracy of the reconstructed spectral reflectance is high, and it saves the analysis time of printing products by using professional spectral analysis instruments, thus completing the quality inspection of printing products quickly and efficiently.

[0085] In this embodiment, since the pre-trained spectral reconstruction model has an autoencoder and a detection network, the autoencoder can encode the spectral reflectance of 31 bands into 8 classes of encoded data and decode the encoded data into the corresponding spectral reflectance. Therefore, it can effectively improve the detection speed of the spectral reconstruction model and further improve its detection accuracy and recognition precision. Furthermore, since the detection network has the function of clustering and sorting multiple color values, it can divide and sort the color values ​​into several ordered color clusters, and train the detection network based on these ordered color clusters. Therefore, it can further improve the accuracy of the spectral reconstruction model and optimize its ability to predict the spectral reflectance of colors not in the training set.

[0086] <Variation Example>

[0087] For ease of explanation, the same symbols are used for structures identical to those in the embodiments in this variation, and the same descriptions are omitted.

[0088] In this embodiment, the detection parameter reconstruction unit 13 reconstructs the color value to be measured using a pre-trained spectral reconstruction model to obtain the reconstructed detection parameters. In contrast, in this modified example, the detection parameter reconstruction unit 13 reconstructs the color value to be measured based on the chromaticity value to obtain the reconstructed detection parameters, specifically:

[0089] The detection parameter reconstruction unit 13 has a standard chromaticity value storage unit and a chromaticity value reconstruction unit.

[0090] The judgment unit 14 has a color value judgment section.

[0091] The standard chromaticity value storage unit stores multiple color values ​​and their corresponding chromaticity values.

[0092] The chromaticity value is either the XYZ value or the LAB chromaticity value.

[0093] The chromaticity value reconstruction unit retrieves the corresponding chromaticity value from the standard chromaticity value storage unit based on the color value to be measured.

[0094] When the chromaticity value reconstruction unit cannot retrieve the corresponding chromaticity value from the standard chromaticity value storage unit based on the color value to be measured, the chromaticity value reconstruction unit uses a difference algorithm to calculate the difference between the color value to be measured and all standard chromaticity values, and then uses the standard chromaticity value with the smallest difference (i.e., the chromaticity value that is closest to the color value to be measured) as the corresponding chromaticity value.

[0095] The colorimetric value judgment unit determines whether the colorimetric value matches the standard colorimetric value.

[0096] When the judgment unit 14 determines that it is not true, the printing control unit 15 adjusts the printing parameters of the printing device according to the chromaticity value and the standard chromaticity value, so that the printing device prints a printed product that meets the predetermined target parameters.

[0097] Modification Example: Function and Effect

[0098] According to the printing product inspection system provided in this variation, since the colorimetric value reconstruction unit retrieves the corresponding colorimetric value from the standard colorimetric value storage unit based on the color value to be measured, and then the colorimetric value judgment unit judges whether the colorimetric value matches the standard colorimetric value, the colorimetric value can be obtained directly from the 1mm wide detection color bar 102, and the quality of the printing product can be evaluated directly based on the colorimetric value and the standard colorimetric value, which is fast, efficient and environmentally friendly.

[0099] The above embodiments and variations are only used to illustrate specific implementations of the present invention, and the present invention is not limited to the scope of the above embodiments.

[0100] In the above embodiments, the product being tested is a paper print. In other embodiments of the present invention, it can also be used for any other form or material, such as liquids or packaging, that requires color detection.

Claims

1. A printing product inspection system for inspecting the color quality of printed products produced by a printing apparatus, characterized in that, include: An image acquisition device is used to acquire images of the printed product to obtain a corresponding target image. The printed product is a paper printed product with a predetermined image and at least one detection color bar. The color value extraction unit extracts the color value of the detected color bar in the target image as the color value to be measured. The detection parameter reconstruction unit is used to reconstruct the corresponding detection parameters based on the color value to be measured, and the reconstructed detection parameters are spectral reflectance. The judgment unit determines whether the reconstructed detection parameters match the predetermined target parameters, wherein the predetermined target parameters are standard spectral reflectance. as well as When the determination unit determines otherwise, the printing control unit adjusts the printing parameters of the printing device according to the reconstructed detection parameters and the predetermined target parameters, so that the printing device prints a product that meets the predetermined target parameters. The image acquisition device includes at least a guide rail and a scanning head. The guide rail transports the printed product to the scanning head, enabling the scanning head to scan the transported printed product and obtain the corresponding target image. The width of the detection color bar is 0.2mm-2mm. The detection parameter reconstruction unit has a model reconstruction section, and the judgment unit has a spectral reflectance judgment section. The model reconstruction section reconstructs the color value to be measured using a pre-trained spectral reconstruction model to obtain the corresponding spectral reflectance. The spectral reflectance judgment section determines whether the spectral reflectance matches the standard spectral reflectance. The pre-trained spectral reconstruction model has an autoencoder and a detection network. The spectral reflectance includes multiple spectral bands and the intensity value of each spectral band. The autoencoder has an encoder for encoding the spectral reflectance having multiple bands into a predetermined number of encoded data, and a corresponding decoder for decoding the encoded data into the spectral reflectance. The detection network was obtained in advance through the following training steps: Step S1-1: Obtain a standard image of the standard printing template by the image acquisition device, wherein the standard image contains multiple standard color blocks; Step S1-2: Obtain the color value of the standard color block as the standard color value and the corresponding spectral reflectance as the standard spectral reflectance; Steps S1-3: Cluster the standard color values ​​and divide the multiple standard color values ​​into several color clusters; Steps S1-4: Sort the standard color values ​​in each color cluster according to their size to form several ordered color clusters. Steps S1-5: Input the standard spectral reflectance corresponding to each standard color value into the encoder in sequence to obtain the corresponding encoded data as standard encoded data; Steps S1-6: According to the order of the standard color values ​​in each ordered color cluster, the initial detection network is trained sequentially based on the standard color value and the corresponding standard encoding data until the predetermined conditions are met and the trained detection network is obtained.

2. The printing product inspection system according to claim 1, characterized in that: in, The spectral reflectance has 31 bands, and the predetermined number of classes is 3 to 12.

3. The printing product inspection system according to claim 2, characterized in that: in, The predetermined quantity can be 3 or 8 categories.

4. The printing product inspection system according to claim 1, characterized in that: in, The reconstructed detection parameter is a chromaticity value, and the predetermined target parameter is a standard chromaticity value. The detection parameter reconstruction unit has a standard chromaticity value storage unit and a chromaticity value reconstruction unit. The judgment unit has a chromaticity value judgment part. The standard chromaticity value storage unit stores multiple color values ​​and their corresponding chromaticity values. The chromaticity value reconstruction unit retrieves the corresponding chromaticity value from the standard chromaticity value storage unit based on the color value to be measured. The chromaticity value determination unit determines whether the chromaticity value matches the standard chromaticity value.

5. The printing product inspection system according to claim 4, characterized in that: in, The chromaticity value is either an XYZ value or a LAB chromaticity value.

6. The printing product inspection system according to claim 1, characterized in that: in, The width of the detection color bar is 0.5 mm or 1 mm.

7. The printing product inspection system according to claim 1, characterized in that: in, The image acquisition device also has a suction plate. The suction plate has multiple suction holes for adsorbing the printed product, so that the printed product is tightly attached to the suction plate.

8. The printing product inspection system according to claim 1, characterized in that, Also includes: The prompting unit generates a prompt that the printed product does not meet the standard when the judgment unit determines that it is not. This prompts the operator to take appropriate action on the printed product.

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