System and method for handling variations in a printed mark

The embodiments herein relate to a method performed by a system (100) for handling variations in a mark (110) printed by a group (105) of industrial printers (101). The system (100) obtains images of the printed mark (110) printed by each of the printers (101) in the group (105). The system (100) creates a composite image from the obtained images. The printed marks (110) appear as a repeating pattern in the composite image. The system (100) compares the printed marks (110) in the composite image to each other or to another mark. The system (100) detects variations with a first resolution in the printed marks (110) in the composite image as a result of the comparison. The system (100) creates an augmented image in which the detected variations are augmented to a second resolution. The first resolution is lower than the second resolution.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a national phase entry under 35 U.S.C. § 371 of International Application No. PCT/EP2019/084806, filed on Dec. 12, 2019, published in English, which claims priority to European Patent Application No. 18212147.5, filed on Dec. 13, 2018, the disclosures of which are hereby incorporated herein by reference.

TECHNICAL FIELD

Embodiments herein relate generally to a system and a method performed by the system. More particularly the embodiments herein relate to handling variations in a mark printed by a group of industrial printers.

BACKGROUND

Industrial printing and coding is a fundamental element of modern production lines with enormous numbers of products across a wide range of industries requiring marking of some form. This marking may range from a simple best before-label to more complex marks that allow data transmission through scanning processes, such as Quick Response (QR) codes and barcodes. According to GS1, the organisation responsible for maintaining barcode standards, over 5 billion barcodes alone are scanned every day.

Variations in the quality of marks produced by an industrial printer can cause reading and scanning errors for the final product, and indicate underlying issues with the printer itself. Common errors including low contrast and mark inconsistency are often associated with incorrect printer settings, e.g. printhead distance, speed etc., printhead problems, e.g. degradation, or substrate incompatibilities. In addition, poor mark quality may indicate a suboptimal printing environment which suffers from contamination by dust or condensation. Mark variation may also remain invisible to a human operator for some time, due to the high resolution of many industrial units enabling very small-scale features to be printed.

Under certain conditions, the human eye is estimated to have a viewing resolution of 170 dots-per-inch (dpi). This value is comparable to the minimum 150 dpi of a typical high-resolution in for example a carton ink jet printing process. However, research suggests that human vision reflects only an approximation of the full content of a scene—a human views only the “gist” of what is visible. This provides limitations to the ability of the human eye to detect variations between visually similar images or marks. Humans are better at detecting change in an image when that image is structured or ordered, rather than its contents randomly distributed throughout.

Techniques have been developed that allow minute variations in visual digital media to be identified and magnified or decreased. Previous research on motion magnification has allowed humans to detect small vibrations in video, enabling the reconstruction of an audio signal associated with the observed vibrations. Leading from this, further research has seen the development of algorithmic methods for augmenting small variations in images of repeating structures. The process takes a single image as input, and searches within that image for repeating patterns. The algorithm then uses these patterns to smooth or amplify differences in colour or geometry across the image. Applications for the method may include visual inspection methods, whereby any defect in a repeating structure may be magnified to ease detection by human or automatic means.

Therefore, there is a need to at least mitigate or solve these issues.

SUMMARY

An objective of embodiments herein is therefore to obviate at least one of the above disadvantages and to provide improved handling of variations in printed marks.

According to a first aspect, the object is achieved by a method performed by a system for handling variations in a mark printed by a group of industrial printers. The system obtains images of the printed mark printed by each of the printers in the group. The system creates a composite image from the obtained images. The printed marks appear as a repeating pattern in the composite image. The system compares the printed marks in the composite image to each other or to another mark. The system detects variations with a first resolution in the printed marks in the composite image as a result of the comparison. The system creates an augmented image in which the detected variations are augmented to a second resolution. The first resolution is lower than the second resolution.

According to a second aspect, the object is achieved by a system for handling variations in a mark printed by a group of industrial printers. The system is adapted to obtain images of the printed mark printed by each of the printers in the group. The system is adapted to create a composite image from the obtained images. The printed marks appear as a repeating pattern in the composite image. The system is adapted to compare the printed marks in the composite image to each other or to another mark. The system is adapted to detect variations with a first resolution in the printed marks in the composite image as a result of the comparison. The system is adapted to create an augmented image in which the detected variations are augmented to a second resolution. The first resolution is lower than the second resolution

Since the printed marks in the composite image are compared to each other or to another mark, variations can be detected and provided with a second resolution in the augmented image. Thus, the handling of variations in the printed marks is improved.

Embodiments herein afford many advantages, of which a non-exhaustive list of examples follows:

One advantage of the embodiments herein is that they enable a human operator to compare a relative printer mark quality within a printer network, facilitating the identification of variations in mark quality between printers and over time. The embodiments herein also allow the operator to visualise the variation in mark quality between printers. Mark variations are typically very small, and while they may affect the ability of a printed mark to be, for example, scanned in a shop, a human operator may not be able to observe the variation optically.

Another advantage of the embodiments herein is that they enable tailored and adaptable selection of printer groups to generate mark variability comparisons that may be used to identify relative differences, ensuring that a uniform mark is produced across all printers in the group. Numerous printer combinations may be automatically selected and compared in order to facilitate the detection of mark variability and identification of its cause.

A further advantage of the embodiments herein is that they enable rapid and intuitive operator identification of mark variation between printers, allowing the operator to initiate improvements or repairs of printers with high mark variability.

Furthermore, an advantage of the embodiments herein is that they enable identification of mark variability early in the printing process, resulting from augmentation of the human operator's ability to detect variation. Losses due to catastrophic mark variation or unexpected downtime for printer maintenance may be prevented as a result.

A further advantage of the embodiments herein is that they enable detection of external factors which otherwise are difficult to detect, e.g. the operating environment around the printer which causes variations in the marks.

The embodiments herein are not limited to the features and advantages mentioned above. A person skilled in the art will recognize additional features and advantages upon reading the following detailed description.

The drawings are not necessarily to scale and the dimensions of certain features may have been exaggerated for the sake of clarity. Emphasis is instead placed upon illustrating the principle of the embodiments herein.

DETAILED DESCRIPTION

Variation in printed marks can indicate underlying machine issues, which may negatively affect the production line due to unscheduled maintenance and product recalls. Detecting variation at an early stage is particularly difficult for human operators, as differences initially might only be observed in a few dots per inch in each mark. The embodiments herein therefore allows grouping of printers in such a way as to detect minute mark variations occurring between the printers, indicating both that variation is occurring and its location in the mark. This allows comparison of the print settings, processes and other environmental factors between the grouped printers to identify the root cause of the variation. By identifying the provenance of mark variations, manufacturers can anticipate maintenance requirements and prevent losses due to product wastage and unplanned downtime.

FIG. 1ais a schematic drawing illustrating an example of a system100. The system100may be any suitable device, mobile or stationary, enabled to be adapted to and to communicate over a communications connection with at least one industrial printer101. The system100may comprise for instance but not limited to e.g. a user equipment, mobile phone, smart phone, sensors, meters, vehicles, household appliances, medical appliances, media players, cameras, Machine to Machine (M2M) device, Internet of Things (IOT) device, terminal device, communication device, tablet computer, laptop or Personal Computer (PC). The system100may be portable, pocket storable, hand held, computer comprised, enabled to communicate voice and/or data, via the communications connection, with another entity, such as another system or a server. The system100may be operated by an operator. The system100may be adapted to execute algorithms or computer programs. The system100may comprise various sub subsystem or modules, and one example of this is illustrated inFIG. 2described below.

The system100is adapted to be connected to one, two or more industrial printers101. An industrial printer101is configured to mark various types of substrates with different types of patterns. This may also be described as the printer101is adapted to print a mark on a substrate or object. One example of an operation of such an industrial printer101is the marking of patterns on various types of packages or consumer goods e.g. on a packaging line or a manufacturing assembly line. The term industrial in industrial printer, industrial printer system and industrial printing may refer to that it is related to or characterized by industry, that it is designed or suitable for use in industry. Industry may be described as the process of making products by using machinery and factories. In industry, the environmental conditions may be variable in time, the ambient temperatures may vary etc. For the sake of simplicity, the term printer101may be used herein when referring to the industrial printer101. The example inFIG. 1aillustrates five printers101, but any other n number of printers101is applicable, where n is a positive integer.

A printer network103comprises a plurality of printers101. Some of the printers101in the printer network103may be grouped in one or more printer groups105. The printer network103is illustrated with the outer dotted box and the printer group105is exemplified with the inner dotted box. InFIG. 1a, the printer network103is exemplified to comprise five printers101, and the printer group105comprises three of the printers101in the printer network103. Two of the printers101in the printer network103exemplified inFIG. 1aare not comprised in any printer group105, but they may be comprised in another printer group105in another example. Even thoughFIG. 1aillustrates an example with one printer group105, any other m number of printer groups105is equally applicable, where m is a positive integer. The printer network103may comprise a larger number of printers101than a printer group105, or the printer network103may comprise the same number of printers101as a printer group105. The group105may be seen as a subset of the printer network103.

Thus, the printer group105is a group of printers101selected from the wider printer network103for comparison to each other. At the time a comparison of printed marks is made, each printer101in the printer group105will be printing the same mark.

The variability of the mark of interest will be used for comparison of the printers101. Mark variability may manifest as differences in parameters comprising for example at least one of:Colour, and/orGeometry, and/or.Opacity etc.

Multiple printer groups105may also be defined, in order to provide in-depth relative information about each printer101compared to its peer printers101. During analysis, a particular printer101may be included in one or more printer groups105. A printer group105may be composed of:Similar printers101within the same factory.Printers101coding the same mark on different substrates.Printers101operating across different factory locations.Printers101controlled and/or maintained by different technicians or operators.Printers101operating at different settings.Other variables from which performance information may be obtained.

The mark printed by printers101in the printer group105may also be compared to prior marks known to have:Low variability, which represent an ideal or optimal version of the mark being analysed.High variability, which represent worst-case versions of the mark being analysed.Been acquired at specific points across the operating period of printers101within the printer group105, e.g. after recalibration, after every 400 marks etc. Specific acquisition points may be used for long-term data tracking, giving an accurate indication of performance with use.

The connection between the industrial printers101and the system100may be a wireless or wired connection. The connection may use any suitable protocol depending on type and level of layer, e.g. as indicated by the Open Systems Interconnection (OSI) model, as understood by the person skilled in the art. The connection may be a direct connection or a connection that goes via some other unit (not shown inFIG. 1a).

The system100and the industrial printers101may be located at substantially the same physical location, or they may be located at different physical locations.

FIG. 1afurther illustrates a user interface108which is adapted to be connected to the system100, or the printer101or to both the system100and the printer101. The user interface108may be integrated in or co-located with the system100or it may be a standalone user interface108adapted to be connected to the system100and/or the printer101. An operator of the system100may view the user interface108. The operator may also interact with the user interface108, e.g. providing commands to the printer101via the user interface108, manipulating images printed by the printers101, initiate setting changes of the printer101etc. The user interface108may also be referred to as a display, a screen, a monitor, a touch screen, an output module etc. The user interface108may comprise various modules and one example of this is illustrated inFIG. 2described below. A trained user may access and control aspects of the mark variability analysis process through the user interface108. The user interface108may be adapted to provide one-way communication to the operator or adapted to provide two-way communication with the operator. Using other words, the user interface108may be non-interactive or interactive. When the user interface108is non-interactive it may be adapted to only display information and data to be viewable by the user, i.e. it is adapted to allow a one-way communication from the system100and/or the printer101to the user. The user interface108may be an interactive user interface in that it is adapted to allow two-way communication between the system100and/or the printer101and the user, i.e. the user interface108responds to the user's input. When the user interface108is an interactive user interface it may comprise an input module and an output module. The user may also be referred to as an operator.

FIG. 1billustrates an example of a mark110printed by the industrial printer101. The mark110may be any mark110suitable to be printed on a substrate (not shown), such as barcode, QR code, image, fonts, graphics, codes, etc. The mark110may be of any suitable size and color. Even though the mark110is exemplified as a barcode inFIG. 1b,any other type of mark110is equally applicable herein.

FIG. 2is a schematic drawing illustrating another example of the system100. The printer group105is exemplified inFIG. 2to comprise five printers101. However, the printer group105may comprise any other suitable n number of printers101, where n is a positive integer. The system100may comprise various sub subsystem or modules such as e.g. a composite image construction module100aand an image variation assessment module100b. The user interface108may comprise various subsystems or modules such as e.g. a visualization module108aand an input selection module108b. The visualization module108amay or may not be comprised in the user interface108. The input selection module108bmay be a standalone module or it may be co-located in the user interface108. The input selection module108bmay be co-located in the user interface108in the form of the user interface108being for example a touch screen, it may be keyboard adapted to be connected to the system100and/or the printer101etc. These modules will be described in more detail with reference toFIGS. 4 and 5below.

The method for for handling variations in a mark110printed by a group105of industrial printers101, according to some embodiments will now be described with reference to the flowchart inFIG. 3. In short,FIG. 3illustrates a process for enabling the identification of relative variability in printed marks110for example via the human eye. It also illustrates adaptive grouping of printers101allowing mark variability to be identified across various machines and locations. An operator of the system100intends to assess mark variability across a particular printer group105, where each printer101in the printer group105is producing substantially the same mark110. The marks110produced by the printer group105may appear identical to the human eye.

The method comprises at least one of the following steps, which steps may as well be carried out in another suitable order than described below:

The operator may access the user interface108and initiates defining of the printer group105and the mark110to be compared, or the system100may initiate defining of the printer group105and the mark110to be compared. The operator may access the user interface108for example via the input selection module108b.

The printer group105may be defined:a) manually by the operator via the user interface108, orb) automatically by the system100, e.g. as a function of the input selection module108b. The system100may automatically define the printer group105based on prescheduled requirements, e.g. weekly or daily checks.

The operator of the system100may identify a specific printer101, the printer group105, the mark110or other parameter(s) for comparison, and the system100may auto-populate the printer group (or groups)105with other printers101in the printer group105.

Information indicating the printer group105may be sent from the input selection module108bof the user interface108to the system100, e.g. to the composite image construction module100ain the system100.

The system100obtains an image from each printer101in the printer group105. The obtained image may be referred to as an output image. This may be done by that the system100, e.g. by the composite image construction module100a, queries the printers101in the printer group105and receives output images from at least some of the printers101. Instead of querying and receiving output images from the printers101, the system100may query and obtain output images from at least one image capturing device (not shown) adapted to capture images of marks printed by the printers101.

A composite image may be constructed from at least some of the output images, or for all output images. For example, the composite image construction module100amay construct the composite image from the output images and may send it to the image variation assessment module100bfor assessment.

The output images from the printers101may also be obtained retrospectively from an image cache or memory associated with each printer101or the system100. The images in the image cache may have been obtained by an image capturing device connected to the printers101. The image cache may store the output images for a certain period of time, e.g. over a 24-hour period, along with sampled images obtained over a longer time span. In this way, reference output image sets are available to the system100, e.g. its composite image construction module100a, that increases the potential range of printer group comparisons and increase the temporal accuracy of fault detection. The image cache may be located in close proximity to the system100, it may be comprised in the system100, it may be adapted to be connected to the system100and/or the printer101, it may be a cloud memory etc.

The system100analyses the composite image to identify, augment and optionally measure color and spatial variation in the composite image. The variations may be of a first resolution. The first resolution may be a subpixel resolution. The first resolution may be such that the variation is invisible to the human eye. The analysis may be done by comparing the output images to each other to identify any variability between them. The detected difference is then optically magnified to make the subtle variations visible to the human eye. When magnified, the variations may be of a second resolution. The first resolution is lower than the second resolution. The second resolution may be a pixel resolution. The second resolution may be visible to the human eye. The analysis may be performed for example by the image variation assessment module100bcomprised in the system100. The analysis results in creation of an augmented image.

Optionally, the variation measurements are also obtained by system100, e.g. by the image variation assessment module100b.

The augmented image is sent from the system100to the user interface108to be displayed with the second resolution. For example, the augmented image may be displayed by the visualization module108a. Optionally, the color and spatial variation measurements may also be sent to the user interface108and displayed to the operator. When at the second resolution, the variations shown by the augmented image may be visible to the human eye of the operator.

The operator views the augmented image, and optionally also the variation measurements, via the user interface108, e.g. via the visualisation module108aof the user interface108.

Optionally, the operator or the system100defines a further composite image subset for further visual analysis based on the assessment of the augmented image. This may be carried out using e.g. a subset generation module, utilised via the user interface108.

FIG. 4is a flow chart illustrating an example of the method for handling variations in a mark110printed by a group105of industrial printers101. The method comprises at least one of the following steps, which steps may be performed in any suitable order than described below:

This step corresponds to step300inFIG. 3. The printer group105may be selected by the operator e.g. using the input selection module108bor it may be automatically selected by the system100itself, in addition to selection of the mark110to be used in the analysis. Information about the printer group105and the mark110is provided to the system100. The input selection module108bmay be a standalone input selection module108bsuch as for example a keyboard, a mouse device, a joystick etc., or it may be co-located with the visualisation module108ain the user interface108. When co-located, the input selection module108bmay be the feature of the user interface108enabling two-way communication between the user and the system100, for example in the form of a touch screen.

In one alternative, the operator may define the parameters of the mark variability analysis process via the user interface108, e.g. via the input selection module108b. This may include:Selecting the printer group105from the printer network103for which printed marks110will be compared.Selecting the mark110which will form the basis of the comparison.

Alternatively, the system100may automatically select the printer group105and/or the mark110and it may be able to identify parameters, equipment and processes for comparison. In this alternative the operator might, for example, identify a specific printer101for which a printed mark110is to be compared. The system100may then identify other printers101currently producing the same mark110and assign them to the printer group105.

Selection of the printer group105may be undertaken by the operator via the user interface108or by the system100upon request or automatically on a predetermined schedule. The printer group105selection may be made based on the specific requirements of the analysis.

The results of the mark variability analysis may be presented to the operator via the user interface108, e.g. via the visualisation module108a. The user interface108, e.g. the visualisation module108a, allows the operator to visually assess and act on any variability between marks110. The results presented may include images, measurements and other relevant data. Other relevant data may include any information which may help to identify the causes of variation, such as temperature, ink brand, dates of previous maintenance etc.

These steps correspond to step310inFIG. 3. The system100, e.g. the composite image construction module100a, uses the printer group information supplied by the user interface108, e.g. the input selection module108b, from step400, to request images of the mark110from each relevant printer101. The images may instead be requested from an image capturing device (not shown) which is adapted to capture the images of the marks110printed by the printers101. Such image capturing device may be a standalone device or it may be co-located in the printer101. The images may be referred to as output images. The output images may be captured by an imaging system built-in to each printer101in the printer group105. The imaging system may produce output images in any sensing modality. Each output image may be tagged with a unique ID number, e.g. a printer ID, allowing the originating printer101to be identified if necessary. Output images may be cached or stored by a printer101or an external memory, e.g. a cloud memory or a system memory, for a certain period of time, allowing past images to be compiled into a reference group as required to provide an assessment of variation over time. Each requested printer101or image capturing device sends the image of the mark110back to the system100.

The system100, e.g. via the composite image construction module100a, is adapted to create a composite image composed of the images of the mark110produced by each of the printers101, e.g. the output images from the printer group105. When more than one printer group105is being compared, a composite image may be produced for each printer group105and tagged with an appropriate image identifier, e.g. a composite image ID.

The comparison undertaken by the system100may take input from a number of printer groups105in order to separate and identify multiple causes of variation, or the development of variation over time. The “comparison” refers to that a number of output images are compared in order to detect variations between them.

The system100, e.g. via the composite image construction module100a, may create a single composite image for each printer group comparison.

The composite image may be constructed such that small variations between the marks110shown in the output images may be visible to the system100. The variations may be of a first resolution, and this may be for example as subpixel resolution. Variations with the first resolution may not be visible to the human eye.

The output images included in each composite image may be automatically varied by the system100via the selection of the printer groups105in such a way as to obtain the required comparison and analysis, i.e. incorporating various comparative parameters and their effects on variability over time.

The marks110in the output images may be shown in full in the composite image, or a smaller mark section, e.g. a mark subsection, may be selected for analysis from the output image. The mark subsection may be automatically selected by the system100, e.g. by the composite image construction module100a. Alternatively, the operator may manually select the mark subsection by using the user interface108.

The marks110or mark subsections in the composite image take the form of an array of repeating structures. Optionally, the system100, e.g. the composite image construction module100a, may incorporate a further component which may enable the system100to correct for or separate different sources of variation. For example, colour variation may be occurring between printers101due to the use of slightly different ink types/levels, but the operator may be searching specifically for a vibration or mark geometry problem.

This step corresponds to step320inFIG. 3. The composite image may be provided from the composite image construction module100ato the image variation assessment module100b. The image variation assessment module100bis a module adapted to assess the composite image for variability of the first resolution between marks110. The image variation assessment module100bmay perform at least one of the following: identification, augmentation and measurement:Identification: The image variation assessment module100bmay detect small variations between marks110in the composite image(s) at the first resolution, e.g. at subpixel resolution, i.e. that are invisible to the human eye.Augmentation: The image variation assessment module100bmay alter the detected variations, augmenting the composite image by magnifying the differences between the marks110. The magnified features are compiled into a new augmented composite image. The term augmented image will be used herein for the sake of simplicity when referring to the augmented composite image. Where more than one printer group105is being compared, an augmented image may be generated for each associated composite image. Optimum augmented images for visual inspection, i.e. resulting from printer group selection combinations, may be automatically constructed at regular intervals or when required and based on numerous factors, such as failure likelihood, use of a new ink type, environmental variations, registered faults or vibration-causing incidents. The augmented image may be of the second resolution, which is higher than the first resolution.Measurement: The image variation assessment module100bmay optionally measure the detected variations compiling data that may be used to precisely quantify the subtle differences between the marks110. The detected variations may be referred to as variation measurements.

A subset of the output images comprised in the composite image may be extracted for further analysis. The subset of the output images may be referred to as a composite image subset. The generation of the subsystem may be performed by a subset generation module (not shown) comprised in the system100.

The subsets may be composed of, for example at least one of:Output images showing a complete mark110.Mark subsections.

The composite image subset may be selected to, for example, target marks110produced by a particular printer101within the printer group105, or a particular mark subsection that is known to be problematic.

The generation of the subset may be initiated after generation of the augmented image(s), in such a way as to allow the operator to visualise specific combinations of images, printers or setting groups. In one alternative, the subset may be generated after an initial manual inspection of the augmented image by the operator when the number of output images comprised in the augmented image is sufficiently small. In another alternative, the subset may be automatically generated, whereby the system100may select those output images exhibiting the greatest variation and combine them with output images within the median variance band to highlight the printers/time periods etc. where the variation is occurring.

This step corresponds to step330inFIG. 3. The outputs from the image variation assessment module100b, i.e. the augmented image and optional the variation measurements, may be transmitted to the user interface108, e.g. the visualisation module108a, where they may be presented in such a way as to allow the operator to intuitively determine the level of mark variability and the originating printer(s)101. Instead of sending the outputs to the user interface108, the outputs may be processed by the system which automatically determines the level of mark variability and the originating printer(s)101, with or without input from the operator.

From this analysis, the operator or the system100may initiate additional actions to deduce the potential cause of the variability. These additional actions may be for example sensor placement and printing parameter adjustment.

A step similar to step504described below may be performed before or after step404, but is not illustrated inFIG. 4.

FIG. 5is a flow chart illustrating an example of the method for handling variations in a mark110printed by a group of industrial printers101. The difference between the examples inFIGS. 4 and 5is in step404and504. In other words, the other steps are the same in both examples. The method comprises at least one of the following steps, which steps may be performed in any suitable order than described below:

This step corresponds to step300inFIG. 3and step400inFIG. 4. The printer group105may be selected by the system100or selected by the operator for example via the input selection module108b, in addition to selection of the mark110to be used in the analysis. Information about the printer group105and the mark110is provided to the system100.

Further details regarding this step are described under step400earlier. The input selection module108bmay be seen as part of the user interface108, as indicated with the dotted box, or it may be a standalone input selection module108b.

This step corresponds to step310inFIG. 3and steps401-402inFIG. 4. The system100, e.g. the composite image construction module100a, uses the printer group information supplied by the user interface108, e.g. the input selection module108b, from step500, to request images of the mark110from each relevant printer101or from an image capturing device (not shown). Each requested printer101or the image capturing device sends the image of the mark110back to the system100.

The system100, e.g. via the composite image construction module100a, is adapted to create a composite image composed of the images of the mark110produced by each of the printers101, e.g. the output images from the printer group105. The composite image is of a first resolution, which is lower than a second resolution of an augmented image described later. The first resolution may be a subpixel resolution.

Further details regarding these steps are described under step401-402above.

This step corresponds to step320inFIG. 3and to step403inFIG. 4. The composite image may be provided from the composite image construction module100ato the image variation assessment module100b. The image variation assessment module100breceives the composite image and creates the augmented image. The image variation assessment module100bmay also obtain variability measurements related to the composite image and/or the augmented image. The variations shown in the augmented image may be of a second resolution which is higher than the first resolution of the composite image. The second resolution may be a pixel resolution. The second resolution enables variations between the images to be visible by the human eye.

Additional details regarding this step are the same as described under step403earlier.

This step may be different from the method exemplified inFIG. 4. The output from the image variation assessment module100b, i.e. the augmented image and optionally the variability measurements, may be transmitted to an additional system component referred to as an output module115where it may be automatically utilised to initiate variability-reducing process adjustments in each printer101or additional investigative steps such as sensor operation. The output module115may be comprised in the user interface108, as indicated with the dotted box, or it may be a standalone output module115.

Using other words, step504may be described as a step where the outputs from the image variation assessment module100b, i.e. the augmented image and optionally the variability measurements, may be utilised to trigger automated processes in the printers101comprised in the printer group105.

When the output module115receives the augmented image and possibly the variation measurements from the image variation assessment module100b, it may trigger one or more processes which may include gathering of sensor data or changing printer settings. The triggered processes may be automated or non-automated. The results of the action initiated by the output module115, e.g. in the form of a data stream or visualisation, status update etc., may be fed back to the user interface108for assessment or approval by the operator or the system100.

A step similar to step404inFIG. 4may be performed before or after step504, but is not illustrated inFIG. 5.

The method described above will now be described seen from the perspective of the system100.FIG. 6is a flowchart describing the present method performed by the system100for handling variations in a mark110printed by a group105of industrial printers101. The method comprises at least one of the following steps to be performed by the system100, which steps may be performed in any suitable order than described herein:

This step corresponds to step300inFIG. 3, step400inFIG. 4and step500inFIG. 5. The system100may obtain an identification of a first industrial printer101.

The identification of the first industrial printer101may be obtained from an operator, from the system100, from another system or from a user interface108.

This step corresponds to step300inFIG. 3, step400inFIG. 4and step500inFIG. 5. The system100may identify at least one second industrial printer101currently printing the same mark110as the first industrial printer101. The first industrial printer101and the second industrial printer101may be comprised in the printer group105.

This step corresponds to step300inFIG. 3, step400inFIG. 4and step500inFIG. 5. The system100may determine which printed mark110the images should be obtained of. The group105may comprise printers101printing the determined mark110.

This step corresponds to step310inFIG. 3, steps401and402inFIG. 4and steps501and502inFIG. 5. The system100obtains images of the printed mark110printed by each of the printers101in the group105.

This step corresponds to step310,401,402,501,502inFIG. 5. The system100creates a composite image from the obtained images. The printed marks110appear as a repeating pattern in the composite image.

This step corresponds to step320inFIG. 3, step403inFIG. 4and step503inFIG. 5. The system100compares the printed marks110in the composite image to each other or to another mark.

The other mark110to which the printed mark110is compared may be at least one of:an original version of the printed mark110, and/ora worst-case version of the printed mark110, and/ora mark110printed by another group105of industrial printers.

This step corresponds to step320inFIG. 3, step403inFIG. 4and step503inFIG. 5. The system100detects variations with a first resolution in the printed marks110in the composite image as a result of the comparison. The variations may be in at least one of: color, geometry and opacity.

This step may comprise detecting the variations' location in the composite. The location may be represented by coordinates in e.g. an x-y coordinate system.

This step corresponds to step320inFIG. 3, step403inFIG. 4and step503inFIG. 5. The system100may measure color variation or spatial variation or both spatial and color variation in the detected variations.

This step corresponds to step320inFIG. 3, step403inFIG. 4and step503inFIG. 5. The system100creates an augmented image in which the detected variations are augmented to a second resolution. The first resolution is lower than the second resolution.

This step corresponds to step320inFIG. 3, step403inFIG. 4and step503inFIG. 5. The system100may determine, based on a printer ID, which printer101in the group105that has printed the mark110in which the variations are detected. Each obtained image may have a printer ID associated with the printer101which printed the mark110.

This step corresponds to step330inFIG. 3and step404inFIG. 4. The system100may display the augmented image on a user interface108.

This step corresponds to step330inFIG. 3, step404inFIG. 4and step504inFIG. 5. The system may initiate a change of printer settings and gathering of sensor data based on the detected variations.

To perform the method steps shown inFIGS. 3, 4, 5 and 5for handling variations in a mark110printed by a group105of industrial printers101, the system100may comprise an arrangement as shown inFIG. 7.

The system100comprises a processor701, an interface703and a memory705, in which memory instructions are stored for carrying out the method steps explained above. The system100communicates via the interface703. The interface703comprises both an external interface, communicating with a transmitter and receiver, and internal interfaces (not shown).

The processor701may comprise at least one of the composite image construction module100aand/or the image variation assessment module100bdescribed above.

The system100is adapted to, e.g. by means of the processor701, obtain images of a mark110printed by each industrial printer101in a group of industrial printers105.

The system100is adapted to, e.g. by means of the processor701, create a composite image from the obtained images. The printed marks110appear as a repeating pattern in the composite image.

The system100is adapted to, e.g. by means of the processor701, compare the printed marks110in the composite image to each other or to another mark. The other mark110to which the printed mark110is compared may be:an original version of the printed mark110, and/ora worst-case version of the printed mark110, and/ora mark110printed by another group105of industrial printers.

The system100is adapted to, e.g. by means of the processor701, detect variations with a first resolution in the printed marks110in the composite image as a result of the comparison.

The system100is adapted to, e.g. by means of the processor701, create an augmented image in which the detected variations are augmented to a second resolution. The first resolution is lower than the second resolution.

The system100may be adapted to, e.g. by means of the processor701, obtain an identification of a first industrial printer101. The identification of the first industrial printer101may be obtained from an operator, from the system100, from another system or from a user interface108.

The system100may be adapted to, e.g. by means of the processor701, identify at least one second industrial printer101currently printing the same mark110as the first industrial printer101. The first industrial printer101and the second industrial printer101may be comprised in the same printer group105.

The system100may be adapted to, e.g. by means of the processor701, determine which printed mark110the images should be obtained of. The group105may comprise printers101printing the determined mark110.

The system100may be adapted to, e.g. by means of the processor701, measure color and/or spatial variation in the detected variations.

The system100may be adapted to, e.g. by means of the processor701, determine, based on a printer ID which printer101in the group105that has printed the mark110in which the variations are detected. Each obtained image may have a printer ID associated with the printer101which printed the mark110.

The system100may be adapted to, e.g. by means of the processor701, display the augmented image on a user interface108.

The system100may be adapted to, e.g. by means of the processor701, initiate a change of printer settings and gathering of sensor data based on the detected variations.

The present mechanism for handling variations in a mark110printed by a group105of industrial printers101may be implemented through one or more processors, such as a processor701in the system arrangement depicted inFIG. 7, together with computer program code for performing the functions of the embodiments herein. The processor may be for example a Digital Signal Processor (DSP), Application Specific Integrated Circuit (ASIC) processor, Field-programmable gate array (FPGA) processor or microprocessor. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the system100. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code can furthermore be provided as pure program code on a server and downloaded to the system100.

A computer program may comprise instructions which, when executed on at least one processor, cause the at least one processor to carry out at least one of the method steps in at least one of theFIGS. 3, 4, 5 and 6. A carrier may comprise the computer program, and the carrier is one of an electronic signal, optical signal, radio signal or computer readable storage medium.

Summarized, the embodiments herein relate to:A system100that enables a human operator to visually identify subtle variations in printed marks110based on the relative performance of grouped printers105.How to identify subtle variations in the quality of a printed mark110based on the relative performance of other printers101.How to group printers101such a way as to create advantageous comparison conditions that allow the operator or the system100to determine the location and cause of mark variation.How to enable an operator or the system100to observe subtle variations in the appearance of printed marks110using e.g. the human eye.How to improve printer fleet management by predicting maintenance requirements based on subtle mark variation between printers101.

The methods described herein may be summarized as follows:An operator or the system100wishes to assess the variation between marks110produced by certain printers101in a printer network103, and identifies the relevant printers101to the system for example through a user interface108.The system100obtains images of marks110produced by each of the relevant printers101, for example via an image capturing device or directly from the printer101, and incorporates them into a first image referred to as a composite image where the printed marks110appear as a repeating pattern. The composite image is of a first resolution, e.g. a subpixel resolution.The system100identifies any variation with a first resolution between the marks110and produces a second image referred to as an augmented image in which those variations are magnified to a second resolution so that they for example may be visible to the human eye. The augmented image is of a second resolution which is larger than the first resolution. The second resolution may be a pixel resolution.The operator may view the augmented image through the user interface108and the operator or the system100may act on any observed variation between the marks110, or the augmented image with the second resolution may be transmitted to the output module115where it may be utilised to initiate variability-reducing process adjustments in each printer101or additional investigative steps such as sensor operation.

Herein, a group of images from different printers101are used. The printers101may be located at different factories.

The embodiments herein provide a method for facilitating, manually or automatically, the selection of relevant printers101for advantageous performance comparison and printer diagnosis. The embodiments herein enable rapid and intuitive analysis of subtle mark variations for example by the human eye of a human operator. The embodiments herein compile images captured by various printers101into a composite image and further into an augmented image which may be suitable for mark variability analysis.

With the term augmented used herein, it is referred to that variations are augmented or magnified compared to in the composite image. In order words, the variations in the augmented image are of a higher resolution that the variations in the composite image.

The embodiments herein are not limited to the above described embodiments. Various alternatives, modifications and equivalents may be used. Therefore, the above embodiments should not be taken as limiting the scope of the embodiments, which is defined by the appended claims. A feature from one embodiment may be combined with one or more features of any other embodiment.

The term “at least one of A and B” should be understood to mean “only A, only B, or both A and B”, where A and B are any parameter, number, indication used herein etc.

It should be emphasized that the term “comprises/comprising” when used in this specification is taken to specify the presence of stated features, integers, steps or components, but does not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof. It should also be noted that the words “a” or “an” preceding an element do not exclude the presence of a plurality of such elements.

The term “configured to” used herein may also be referred to as “arranged to”, “adapted to”, “capable of” or “operative to”.

It should also be emphasised that the steps of the methods defined in the appended claims may, without departing from the embodiments herein, be performed in another order than the order in which they appear in the claims.