Coating material testing using image analysis

Abstract

A plurality of images captured during a coating material / substrate breakthrough testing process can undergo image analysis, and a binary threshold can be applied to the plurality of images. A determination of breakthrough of the substrate through the coating material can be determined, and a bounding rectangle can be placed around to the breakthrough to determine an end of breakthrough testing.

Description

TDCC#86389-WO-PCTCOATING MATERIAL TESTING USING IMAGE ANALYSISTechnical Field

[0001] The present disclosure relates to testing coating materials using image analysis. Such a technique can be useful to automate testing of coating materials in accordance with performance standards (e.g., ASTM International standards) and automate experiment end point determinations in accordance with the performance standards, as well as allowing for coating material testing using tinted coating materials, tinted substrates, or a combination thereof.Background

[0002] Coating materials can include a liquid, paste, powder, or other material that is applied to a surface to create a film with a specific purpose. Coating materials can be protective, decorative, or have other specific properties. Coating materials are applied in a thin film to provide protection or decoration to a surface, with most films being thin in comparison to the workpiece / substrate. A coating material formulation is considered in relation to the workpiece / substrate characteristics, surface preparation, application technique and curing method.

[0003] Coating materials can be formulated from a wide variety of chemicals and materials or a combination of different chemicals. Each component in the formulation serves a specific function. Components may include, for instance pigments, additives, binders, and a carrier fluid or solvent, among other components. Example coating materials include paints, lacquers, anticorrosion coatings, surface coating sealants, waterproofing coatings, anti -reflective coatings, flame retardant coatings, etc.Summary of the Disclosure

[0004] The present disclosure relates to coating material testing using image analysis. Coating material testing can include scrubbing a coated surface until breakthrough is determined. Breakthrough can include the point at which the surface, known as the substrate (e.g. a vinyl substrate), can be seen through the coating material. In some examples, breakthrough is determined when a certain amount of the substrate, such as a threshold width and height, are visible. The threshold width and height may be determined by a standard, for example.TDCC#86389-WO-PCT

[0005] Coating material testing using image analysis as described herein allows for automation of the coating material testing process, as well as allowing for testing of tinted coatings, such as tinted paints. This can decrease an amount of time spent manually testing and observing breakthrough of coating materials. Further, testing of tinted coatings is important as tinting of coating materials can change performance of the coating material. For instance, tints (e.g. colorants) may include surfactants, stabilizers, etc. that may affect the coating material formulation. As such, a coating material in white may not perform the same as a coating material having a tint. Testing a tinted coating material allows for testing of the coating material durability to determine if the tint formulations negatively affect the coating material’s scrubbability. In addition, coating material testing using image analysis as described herein allows for the use of different colors of substrates, such that the coating material testing can be user driven and adaptable to different combinations of coating materials and substrates.

[0006] Image analysis, such as machine vision image analysis, can be used to automate decision making within a specific region of interest. Algorithms can accept images and associated parameters as inputs and output requested information. A machine vision image analysis algorithm, as used herein, can allow for rapid analysis of images and determination of end points for experiments in accordance with standard coating material test methods. The adaptive nature of the machine vision image analysis algorithm enables the analysis of a wide range of tinted coating materials. The adaptive nature of the machine vision image analysis algorithm centers around dynamic thresholding parameters (e g., different binary threshold values for different coating material / substrate combinations) based on a tinted coating material and associated substrate. Parameters can be fined-tuned before implementation in the machine vision image analysis algorithm, and users can receive visual feedback on how their changes directly impact the image analysis and associated data outputs. Users may also have access to automated exposure and color calibration, and image data collected in association with the coating material testing can be saved along with timelapse videos.

[0007] The above summary of the present disclosure is not intended to describe each disclosed embodiment or every implementation of the present disclosure. The description that follows more particularly exemplifies illustrative embodiments. In several places throughout the application, guidance is provided through lists of examples, which examples can be used inTDCC&86389-WO-PCTvarious combinations. In each instance, the recited list serves only as a representative group and should not be interpreted as an exclusive list.Brief Description of the Drawings

[0008] Figure 1 is a block diagram illustrating an example scrub cluster laboratory configuration.

[0009] Figure 2A illustrates an example user interface display.

[0010] Figure 2B illustrates another example user interface display.

[0011] Figure 3 A illustrates a method flow diagram for image analysis.

[0012] Figure 3B illustrates examples of coating materials with applied image analysis.

[0013] Figure 4 illustrates an example of a machine-readable medium for coating material testing using image analysis.

[0014] Figure 5 is an example of a system including a device for coating material testing using image analysis.

[0015] Figure 6 is another example of a system including a device for coating material testing using image analysis.

[0016] Figure 7 illustrates an example machine within which a set of instructions, for causing the machine to perform various methodologies discussed herein, can be executed.Detailed Description

[0017] Coating materials can be designed to meet particular standards, for instance voluntary or mandatory technical international standards such as ASTM International standards. The standards can be developed within committees to create consistency and safety within a plurality of products. An examples standard is ASTM International standard D2486 (ASTM D2486).

[0018] ASTM D2486 is a standard method to measure the scrub resistance of coating materials such as wall paints. Put another way, ASTM D2486 includes a procedure for determining the resistance of a coating material to erosion caused by scrubbing. Coated surfaces are tested for resistance to abrasion in several ways. An example includes the use of an abrasion tester under repeatable, controlled conditions that may simulate everyday use and wear patterns.TDCC#86389-WO-PCTThe ASTM D2486 scrub test includes the use of an abrasion testing device with a bristle brush and an abrasive scrub medium. Test methods can include a cycles-to-failure approach on a test coating material and / or a ratio expressed as a percentage of cycles-to-failure obtained on the test coating material to that obtained on a concurrent run with a known reference coating material.

[0019] Some approaches to coating material testing include the use of white coating materials and black substrate materials during testing. This contrast allowed for easier identification of breakthrough of the substrate through the coating material as a result of scrubbing the coating material. As such, associated image analysis methods are restricted to white coating materials. Further, because only white coating materials are used, analysis of tinted coating material requires operator determination of the scrub performance, which can be a large source of test variability due to the subjectivity. Operator observation of the testing end points for tinted coating material experiments may also limit operator productivity. Tinted coating materials are not tested this way, as colors tend to lessen contrast between the coating material and the substrate.

[0020] In contrast, examples of the present disclosure allow for the ability to test and analyze scrub resistance of tinted coating materials. Using image analysis, testing of tinted coating materials can have statistically similar results as testing of white coating materials, and the process may be automated, improving accuracy, efficiency, and allowing for automatic endpoint detection. In addition, progression images and timelapse videos may be created for further analysis of the tinted coating materials and performance of the coating material when tinted. Further, binary threshold values can be determined for tinted coating material and substrate combinations and can be saved for future testing of the combinations.

[0021] As used herein, the singular forms “a”, “an”, and “the” include singular and plural referents unless the content clearly dictates otherwise. Furthermore, the word “may” is used throughout this application in a permissive sense (i.e., having the potential to, being able to), not in a mandatory sense (i.e., must). The term “include,” and derivations thereof, mean “including, but not limited to.” The term “coupled” means directly or indirectly connected and, unless stated otherwise, can include a wireless connection.

[0022] As will be appreciated, elements shown in the various embodiments herein can be added, exchanged, and / or eliminated so as to provide a number of additional embodiments of the present disclosure. In addition, as will be appreciated, the proportion and the relative scale of theTDCC#86389-WO-PCTelements provided in the figures are intended to illustrate certain embodiments of the present invention and should not be taken in a limiting sense.

[0023] Figure 1 is a block diagram illustrating an example scrub cluster laboratory configuration 120. The configuration 120 can include a plurality of scrub cluster scrubbing units such as the units 121, 123, 125, and 127. The scrub clusters can be in pairs, such as scrub cluster pair 126-1 and 126-2. In some examples, more than two scrub cluster pairs 126 may be present in the configuration 120. Each of the scrub clusters units 121, 123, 125, 127 includes a means to hold a substrate (e.g., a substrate having a coating material thereon), and a means to hold and move a brush or other tool across the substrate in a consistent manner to test the scrub resistance of the coating material. The scrub cluster units 121, 123, 125, 127 may be adjustable, for instance, to adjust a rate at which the brush or other tool interacts with the substrate. The scrub cluster units 121, 123, 125, 127 can be communicatively coupled to a user interface and computing device 128. The user interface, in some examples, can be a display of the computing device 128. In some examples, the configuration 120 can include a camera coupled to the computing device and / or a scrub cluster pair 126. The camera can be used to take progressional images of the coating material during testing, which may be used to create a timelapse video of the coating material testing process. The camera, for instance, can be a machine vision camera, which allows for image capturing and testing without having to dye media.

[0024] Each scrub cluster pair 126 may include a pump 124-1, 124-2 or pumps and a media mixer 122-1, 122-2. In some examples, more than one pump 124-1, 124-2 may be present at each scrub cluster pair 126. For instance, each unit 121, 123, 125, 127 can have its own pump. The media mixer 122-1, 122-2 ensures that the scrub media remains well-mixed during the testing process. The scrub media can include water, a defoamer, and an abrasive scrub media. The media mixer 122-1, 122-2 allows for consistency during the testing process. The pump 124-1, 124-2 (e.g., a peristaltic pump) dispenses the abrasive scrub media onto the center of the coating material sample at set intervals. As noted, in some embodiments, each scrub cluster unit 121, 123, 125, 127 can have its own individual pump, while each scrub cluster pair 126-1, 126-2 can share a media mixer. For instance, the unit 125 can have a pump 124-2 and the unit 127 can have its own pump (not illustrated in Figure 1), but the units 125, 127 share the media mixer 122-2. The pumps (e.g., pump 124-2 and a pump for unit 127) draw material from the shared media mixer 122-2.TDCC#86389-WO-PCT

[0025] The configuration 120 may also include an uninterruptible power supply (UPS) 129. This can be coupled to the computing device and allows the system to continue running in the event of a power outage. During scrub testing, a coating material to be evaluated can be applied to a substrate at a particular thickness and allowed to dry according to particular standards. The substrate with the coating material is placed into the scrub cluster and tested. Without image analysis as provided herein, the testing is performed for a pre-determined number of cycles. The number of cycles may be selected based on the type of coating material or the end-use of the coating material or based on a set number of cycles. During testing, the coating material can be observed periodically for visual signs of wear / failure. Breakthrough, (e.g., failure of a coating material) may be revealed as a change in the color. Without image analysis as provided herein, the testing, if there are no early indications of wear, continues until the agreed upon number of cycles is complete. However, such approaches that do not include image analysis may not allow for testing of tinted coating materials, and such approaches may not allow for user data review and input, among other user interactions.

[0026] In some embodiments, the computing device 128 can have instructions stored thereon that are executed to receive a plurality of images during a coating material / substrate breakthrough test process. For instance, a scrub test can be performed at one or more of the scrub clusters pairs 126. A camera in communication with the computing device 128 can capture these images continuously during testing. As used herein, continuously capturing can include capturing images without meaningful breaks. In some examples, the images can be captured at particular intervals.

[0027] The instructions can be executed to do a frame-by-frame analysis of the plurality of images during which identification of a region of interest of the coating material can be identified. This region may include the area that receives the majority of the scrubbing applied thereto, or it may include an area of the coating material of particular interest to the user, among other possible regions of interest.

[0028] The images can have a binary threshold applied thereon, which can transform a color image to a binary image (e.g., black and white), which makes the breakthrough and identification of coating material and substrate easier and more accurate. For instance, if the substrate is viewed as black and the coating material white, as the substrate comes through due to the coating material scrubbing away, the contrast created by the binary threshold makes theTDCC 86389-WO-PCTbreakthrough more identifiable. The binary threshold, for instance, can be defined on a scale of 0-255, with 0 being black and 255 being white. In some examples, binary threshold values are preset, for instance when a particular color combination has been previously tested. If coating material tinted red was previously tested on a blue substrate, any findings and threshold values are saved, so those binary threshold values can be used in the future. If similar tints are use, previously stored binary threshold values may be utilized as starting points.

[0029] Contour mapping (also referred to as “contouring”) can be performed on the images, which allows for viewing of continuous region of breakthrough. The contouring can stipulate a certain height and width for the breakthrough region (e.g., based on an ASTM standard). In some examples, a standard may specify the height and width of the breakthrough region, not just the area, which can be identified with a bounding rectangle, as described further herein. The images, and particularly the region of interest, can be constantly monitored, and once the breakthrough region reaches a particular size (e.g., based on ASTM D2486), an end of testing can be determined.

[0030] Figure 2A illustrates an example user interface display. The user interface display may be communicatively coupled to the computing device and can allow a user to view and analyze the coating material testing process while it occurs. A user can receive visual feedback from multiple camera streams 232 (e.g., four). The camera streams 232 can provide images of the same coating material at different stages of the testing process, allowing a user to witness when, how, and where breakthrough is occurring. Additionally, a user input area 230 allows for a customization of experiment parameters including coating material tine, and run options (e.g., number of scrub cycles, scrub media dispensing rates, binary threshold values, etc.). Results of the testing, as well as preferences from previous or current testing can be displayed and modified via the user interface display, as well.

[0031] Figure 2B illustrates another example user interface display 234. The display 234 illustrates at 236 a first indication of breakthrough (“first cut”) of the tinted coating material and a complete breakthrough (“cut thru”). At 238, the display illustrates the first indication of breakthrough (“first cut”) of the tinted coating material and a complete breakthrough (“cut thru”) on images that have undergone binary thresholding to increase visual contrast between the coating material and the substrate. The display 234 also includes data regarding the first cut andTDCC 86389-WO-PCTfirst cut through, as well as interactive elements for the user, for example an image selector and an option to save results and create videos (e.g., timelapse videos).

[0032] Figure 3 A illustrates a method flow diagram 341 for image analysis. Image analysis used during coating material testing can improve images of the coating material during testing, which can improve testing result accuracy and consistency. For instance, image analysis can allow a user to find pixel intensity values from an image, fine tune analysis parameter values, adjust a region of interest via a drag and drop control, and review an impact of parameter modifications as the modifications are made. A user can enter desired parameter values (e.g., bounding rectangle size, binary threshold values, etc.) via an interactive user interface, and image analysis can be run using the parameters to make breakthrough determinations and end of experiment determinations, among others.

[0033] For instance, a raw image with a region of interest is illustrated at box 340. While illustrated in grayscale in Figure 3A, this image can be in color and includes the coating material at or near breakthrough in the region of interest. For instance, box 340 may include an image of a deep blue coating material on a white substrate. A Gaussian filter may be applied to the image in box 340 to create a smoother and / or sharper image. Binary thresholding can be applied as illustrated at box 342, which can increase the contrast between the substrate and the coating material. Put another way, the region of interest where most of the scrubbing happens is converted into black and white - the deep blue coating material is converted to white, and the white substrate is converted to black. This is based on binary threshold numbers, and the increase in contrast can increase an accuracy of a breakthrough determination. A contour function can be applied to emphasize the area of breakthrough, and a bounding box is used to determine the size of the area that has broken through. Box 344 illustrates the bounding box and also illustrates that using image analysis on the region of interest can increase the clarity and focus of an image as compared to before to image analysis, which can improve accuracy in breakthrough determinations.

[0034] Figure 3B illustrates examples 346, 348, 343 of coating materials with applied image analysis. In the examples 346, 348, 343, different combinations of coating material and substrate have been testing using a same algorithm, but with different binary thresholding values to determine the coating materials vs. the substrate. Based on threshold values, The examplesTDCC#86389-WO-PCTcontrast can be enhanced and clarity given to raw images to improve accuracy and consistency of breakthrough testing, particularly with tinted coating materials and / or substrates.

[0035] Figure 4 illustrates an example of a machine-readable medium 450 for coating material testing using image analysis. The machinereadable medium 450 can be communicatively connected to a processor resource 471 by a communication path 472. In some examples, a communication path 472 can include a wired or wireless connection that can allow communication between devices and / or components within a single device. As used herein, the processor resource 471 can include, but is not limited to: a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a metal-programmable cell array (MPCA), a semiconductor-based microprocessor, or other combination of circuitry and / or logic to orchestrate execution of instructions 473, 474, 475, 476, 477. In a specific example, the processor resource 471 utilizes a non-transitory computer-readable medium 450 storing instructions 473, 474, 475, 476, 477 that, when executed, cause the processor resource 471 to perform corresponding functions.

[0036] The machine-readable medium 450 may be electronic, magnetic, optical, or other physical storage device that stores executable instructions. Thus, a non-transitory machine-readable medium (MRM) (e.g., machine-readable medium 450) may be, for example, a non-transitory MRM comprising Random-Access Memory (RAM), read-only memory (ROM), an Electrically Erasable Programmable ROM (EEPROM), a storage drive, an optical disc, and the like. The machine-readable medium 450 may be disposed within a controller and / or computing device. In this example, the executable instructions 473, 474, 475, 476, 477 can be “installed” on the device. Additionally, and / or alternatively, the machine-readable medium 450 can be a portable, external, or remote storage medium, for example, which allows a computing system to download the instructions 473, 474, 475, 476, 477 from the portable / external / remote storage medium. In this situation, the executable instructions may be part of an “installation package”.

[0037] The machine-readable medium 450 includes instructions 473 to receive a plurality of images during a coating material / substrate breakthrough test process. The coating material can be a tinted coating material, the substrate can be a tinted substrate, or both the coating material and the substrate may be tinted. A camera in communication with the machine-readable medium 450 can capture images of the coating material and substrate being tested. The camera can be a color camera such as a machine vision camera (e g., Gig-E camera). A machine visionTDCC#86389-WO-PCTcamera can provide visual feedback to help a computing device make decision based on what is seen via the camera.

[0038] The plurality of images can be captured and received continuously or periodically (e.g., at certain time intervals). The machine vision camera can allow for clearer and more precision images of the tinted coating material and / or substrate as compared to other cameras and / or analog black and white cameras. The camera may stop capturing images when an end of testing determination has been made, or the camera may continue to capture images for a particular period of time following the determination. In some examples, the captured images may undergo image analysis to determine a region of interest in the coating material and to clarify or crop images. Color calibration may also be performed on each of the plurality of images, in some examples, to adjust a computing device’s color (e.g., via a user interface display) to ensure it displays colors accurately. This allows for consistency in thresholding numbers, as an uncalibrated image (e.g., having inaccurate color) may show different results than a calibrated image.

[0039] The machine-readable medium 450 includes instructions 474 to apply a binary threshold to each one of the received plurality of images. Binary thresholding can include converting a color or grayscale image into a binary image by setting a threshold value. Pixels with intensities above or below the threshold are classified as black or white, respectively. This can aid in image enhancement, edge detection, and pattern recognition, among others, allowing for clearer distinction between the substrate and the tinted coating material.

[0040] The machine-readable medium 450 includes instructions 475 to perform contour mapping on each one of the received plurality of images. Color contour mapping can include, for instance, using color to show the level of variation in parts during deviation (e.g., difference between substrate and coating material) and may include applying a Gaussian filter to each one of the received plurality of images to make the image smoother and remove unwanted artifacts. Darker tones may be used to add depth to areas that you want to appear softer or more drawn in (e.g., the substrate) and lighter shades may be used to enhance other areas or make them appear brighter (e.g., the coating material). This can create additional distinction between the coating material and the threshold in the plurality of images.

[0041] The machine-readable medium 450 includes instructions 476 to determine a continuous region of breakthrough of substrate through coating material during the test processTDCC#86389-WO-PCTbased on image analysis of the mapped plurality of images, and the machine-readable medium 450 includes instructions 477 to surround the continuous region of breakthrough with a bounding shape in response to the continuous region of breakthrough reaching a threshold height and width. In some instances, the bounding shape is a bounding rectangle based on ASTM International standard D2486.

[0042] For example, standards such as ASTM D2486 include particular sizes and shapes of visible substrate before breakthrough is complete. The bounding rectangle may be set to a very similar or same shape and size as required by the standard. For instance, end point detection and determination may be made when the breakthrough is an approximate, predetermined size (e.g., 160 pixels x 10 pixels. The bounding rectangle can be set to these dimensions, so that identification of an end point is more recognizable. In some examples, pixel dimensions are converted to inches, centimeters, or another unit of measurement in accordance with a standard, and the bounding rectangle can be the smallest rectangle that forms around the continuous breakthrough. In some embodiments, a bonding rectangle can automatically appear around the breakthrough when the threshold size is reached.

[0043] In some embodiments, the machine-readable medium 450 can include instructions to receive the plurality of images from a camera coupled to the processor, save the plurality of images to a memory device, and generate a timelapse video utilizing the saved plurality of images. For instance, as the camera collects images, they can be saved and a timelapse video of the images can be put together for evaluation. This can aid a user in determining when and where breakthrough started and ended, if breakthrough was determined too late, if certain parts of the coating material were worn faster than others, evenness of breakthrough, defects in the coating material or substrate, how many cycles it took to reach breakthrough, etc.

[0044] In some embodiments, the machine-readable medium 450 can include instructions to prompt a user for feedback and adjust the threshold size and shape based on the user feedback. For example, binary threshold numbers can be adjusted if the images are not clear enough, if study of the physical coating material / substrate combination appears different than the images on the display, etc. These can be changed before, after, and / or during testing. Because coating material tints vary, and the color of the substrate may vary, the binary threshold numbers may vary based on the chosen coating material and substrate.TDCC#86389-WO-PCT

[0045] In some embodiments, a user can choose their coating material and substrate combination before testing starts. If a test has been previously performed on that combination, binary threshold values that have been used successfully before may automatically be provided, to allow for quick and accurate testing. However, a user may choose to enter different threshold numbers or adjust them based on test results or other preferences. In some examples, the binary threshold values may be provided as a starting point for the user based on past testing.

[0046] Figure 5 illustrates an example of a system including a device 580 for coating material testing using image analysis. In some examples, the device 580 is a computing device that includes a processor resource 571 and a machine-readable medium 580 to store instructions 584, 586, 587, 588, 589, 590 that are executed by the processor resource 571 to perform particular functions. The system can include a plurality of scrub clusters 582 communicatively coupled to the device 580 and a user interface 583 communicatively coupled to the device 580. Figure 5 illustrates how a computing device can execute instructions to perform functions described herein.

[0047] The device 580 includes instructions 584 stored by the machine-readable medium 580 that are executed by the processor resource 571 to continuously capture a plurality of images of a coating material previously applied to a substrate as the coating material undergoes a coating material / substrate breakthrough test process. The test process can include scrubbing a tinted coating material that has been applied to a substrate until failure of the coating material (e.g., breakthrough). The test process can utilize scrub cluster pairs, wherein the scrub cluster units 582 can use equipment in accordance with particular standards, such as a test process brush in accordance with ASTM International standard D2486. In some embodiments, the system can include a programmable logic controller (PLC) to count test process brush strokes, and this information can be saved for future breakthrough determinations.

[0048] The device 580 includes instructions 586 stored by the machine-readable medium 550 that are executed by the processor resource 571 to display, via the user interface 583, visual feedback of the continuously captured plurality of images. Using a machine vision camera allows for the capture visual information from the surrounding environment, under potentially challenging lighting conditions, and provide high-resolution images with precise color accuracy and optimal resolution, The machine vision camera may help machines or computing devices make decisions based on what they see, meaning feedback can be provided to a computingTDCC#86389-WO-PCTdevice based on the images captured by the machine vision camera and displayed via the user interface 583.

[0049] The device 580 includes instructions 587 stored by the machine-readable medium 550 that are executed by the processor resource 571 to apply a binary threshold to the continuously captured plurality of images. Utilizing the feedback, a region of interest in each one of the plurality of images can be determined, and the binary threshold can be applied to those images with the identified region of interest. The binary threshold may be set or may be adjusted based on the feedback received, as well as a user’s previous use of the tinted coating material, among other bases.

[0050] The device 580 includes instructions 588 stored by the machine-readable medium 550 that are executed by the processor resource 571 to analyze the continuously captured plurality of images using image analysis to determine breakthrough of substrate during the test process. The image analysis includes color calibration and contour mapping of the regions of interest. In some examples, the camera analysis, region of interest determination, and the binary threshold application can be part of the image analysis.

[0051] The image analysis can clarify and better differentiate the substrate from the tinted coating material, allowing for a breakthrough determination to be made. Once the determination is made, the device 580 includes instructions 589 stored by the machine-readable medium 550 that are executed by the processor resource 571 to surround the breakthrough with a bounding rectangle. The bounding rectangle can be a distinctive color, for instance bright pink, and it can surround the region of interest where breakthrough has occurred.

[0052] The device 580 includes instructions 590 stored by the machine-readable medium 550 that are executed by the processor resource 571 to detect an end of the test process in response to the breakthrough reaching a threshold height and width. The threshold height and width, for instance, can be the size of the bounding rectangle, and the size of the bounding rectangle may be dependent on industry standards for coating material scrub testing, for instance.

[0053] In some embodiments, the machine-readable medium 550 can store instructions that are executed by the processor resource 571 to display, via the user interface 583, parameters that may be adjusted before the test process, during the test process, or both. The parameters, for instance, can include a coating material tint, breakthrough test process cycles (e.g., how many times to scrub the coating material), brush stroke counts, and binary threshold values, amongTDCC#86389-WO-PCTothers. In some embodiments, the machine-readable medium 550 can store instructions that are executed by the processor resource 571 to display, via the user interface 583, an option to adjust a region of interest using drag and drop control. For instance, if the region of interest has been determined, but the coating material begins to breakthrough elsewhere at a greater pace, a user can shift the region of interest within the plurality of images.

[0054] Figure 6 is another example of a system including a device 660 for coating material testing using image analysis. In some examples, the device 660 is a computing device that includes a processor resource 671 and a machine-readable medium 650 to store instructions 661, 662, 663, 664, 665, 667 that are executed by the processor resource 671 to perform particular functions. The system can include a plurality of scrub cluster pairs 668-1,... , 668-n communicatively coupled to the device 660. Figure 6 illustrates how a computing device can execute instructions to perform functions described herein.

[0055] The device 660 includes instructions 661 stored by the machine-readable medium 650 that are executed by the processor resource 671 to continuously capture a plurality of images of a tinted coating material previously applied to a substrate as the coating material undergoes a coating material / substrate breakthrough test process. In some examples, each one of the plurality of scrub cluster pairs 668 comprises a camera, such as a machine vision camera, to continuously capture the plurality of images.

[0056] The device 660 includes instructions 662 stored by the machine-readable medium 650 that are executed by the processor resource 671 to display, via a user interface of the computing device, visual feedback of the continuously captured plurality of images, and the device 660 includes instructions 663 stored by the machine-readable medium 650 that are executed by the processor resource 671 to apply a binary threshold to the continuously captured plurality of images. The visual feedback can include feedback from machine vision cameras used to capture the images, and the binary threshold allows for a determination of what is the substrate and what is the coating material, so as more and more of the substrate shows through, it is easier to identify breakthrough (e.g., see black coming through white). In some embodiments color calibration on each of the plurality of images can be performed prior to applying the binary threshold to further differentiate the substrate and the coating material.

[0057] The device 660 includes instructions 664 stored by the machine-readable medium 650 that are executed by the processor resource 671 to perform image analysis on theTDCC#86389-WO-PCTcontinuously captured plurality of images. The image analysis can include determining pixel intensity values from each one of the continuously captured plurality of images, analyzing parameter values associated with each one of the continuously captured plurality of images, and determining breakthrough of substrate during the test process based on the pixel intensity values and parameter analysis. The analysis can include contouring (also known as contour analysis) to determine a continuous region of breakthrough in the coating material, in some embodiments.

[0058] The device 660 includes instructions 665 stored by the machine-readable medium 650 that are executed by the processor resource 671 to surround the breakthrough with a bounding rectangle, and the device 660 includes instructions 667 stored by the machine-readable medium 650 that are executed by the processor resource 671 to detect an end of testing in response to the breakthrough reaching a threshold height and width (e.g., in line with particular standards). For instance, the bounding rectangle may be created at desired specifications to make sure the amount of breakthrough meets standards. Once that size is reached, the end of testing can be automatically determined. The testing can continue if the breakthrough is not large enough.

[0059] Figure 7 illustrates an example machine 700 within which a set of instructions, for causing the machine 700 to perform various methodologies discussed herein, can be executed. In various embodiments, the machine 700 can be analogous to a controller. In alternative embodiments, the machine 700 can be connected (e.g., networked) to other machines in a LAN, an intranet, an extranet, and / or the Internet. The machine 700 can operate in the capacity of a server or a client machine in client-server network environment, as a peer machine in a peer-to-peer (or distributed) network environment, or as a server or a client machine in a cloud computing infrastructure or environment.

[0060] The machine 700 can be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a server, a network router, a switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while a single machine 700 is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.TDCC#86389-WO-PCT

[0061] The example machine 700 includes a processing device 702, a main memory 704 (e g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM), etc.), a static memory 706 (e.g., flash memory, static random access memory (SRAM), etc.), and a data storage system 708, which communicate with each other via a bus 710.

[0062] The processing device 702 represents one or more general -purpose processing devices such as a microprocessor, a central processing unit (CPU), or the like. More particularly, the processing device can be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or a processor implementing other instruction sets, or processors implementing a combination of instruction sets. The processing device 702 can also be one or more specialpurpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. The processing device 702 is configured to execute instructions 718 for performing the operations and steps discussed herein. The machine 700 can further include a network interface device 712 to communicate over the network 714.

[0063] The data storage system 708 can include a machine-readable storage medium 716 (also known as a computer-readable medium) on which is stored one or more sets of instructions 718 or software embodying any one or more of the methodologies or functions described herein. The instructions 718 can also reside, completely or at least partially, within the main memory 704 and / or within the processing device 702 during execution thereof by the machine 700, the main memory 704 and the processing device 702 also constituting machine-readable storage media.

[0064] In one embodiment, the instructions 718 include instructions to implement functionality corresponding to coating material testing using image analysis described herein. While the machine-readable storage medium 716 is shown in an example embodiment to be a single medium, the term “machine-readable storage medium” should be taken to include a single medium or multiple media that store the one or more sets of instructions. The term “machine-readable storage medium” shall also be taken to include any medium that is capable of storing or encoding a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present disclosure. The term “machine-TDCC 86389-WO-PCTreadable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media, and magnetic media.

[0065] Although specific embodiments have been described above, these embodiments are not intended to limit the scope of the present disclosure, even where only a single embodiment is described with respect to a particular feature. Examples of features provided in the disclosure are intended to be illustrative rather than restrictive unless stated otherwise. The above description is intended to cover such alternatives, modifications, and equivalents as would be apparent to a person skilled in the art having the benefit of this disclosure.

[0066] The scope of the present disclosure includes any feature or combination of features disclosed herein (either explicitly or implicitly), or any generalization thereof, whether or not it mitigates any or all of the problems addressed herein. Various advantages of the present disclosure have been described herein, but embodiments may provide some, all, or none of such advantages, or may provide other advantages.

[0067] In the foregoing Detailed Description, some features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the disclosed embodiments of the present disclosure have to use more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.

Claims

TDCC 86389-WO-PCTClaimsWhat is claimed is:

1. A system, comprising:a plurality of scrub clusters;a user interface communicatively coupled to the plurality of scrub clusters; and a computing device communicatively coupled to the plurality of scrub clusters and the user interface, the computing device having instructions stored thereon executed to:continuously capture a plurality of images of a coating material previously applied to a substrate as the coating material undergoes a coating material / substrate breakthrough test process;display, via the user interface, visual feedback of the continuously captured plurality of images;apply a binary threshold to the continuously captured plurality of images; analyze the continuously captured plurality of images using image analysis to determine breakthrough of substrate during the test process;surround the breakthrough with a bounding rectangle; anddetect an end of the test process in response to the breakthrough reaching a threshold height and width.

2. The system of claim 1, comprising the instructions executed to display, via the user interface, parameters that may be adjusted before the test process, during the test process, or both.

3. The system of claim 2, wherein the parameters include a coating material tint and breakthrough test process cycles.

4. The system of claim 1, wherein the testing process utilizes a test process brush in accordance with ASTM International standard D2486.TDCC 86389-WO-PCT5. The system of claim 1, wherein the system further comprises a programmable logic controller (PLC) to count test process brush strokes.

6. The system of claim 1, comprising the instructions executed to display, via the user interface, an option to adjust a region of interest (ROI) using drag and drop control.

7. The system of claim 1, comprising:the computing device having instructions stored thereon executed to:perform image analysis on the continuously captured plurality of images, wherein the image analysis comprises:determining pixel intensity values from each one of the continuously captured plurality of images;analyzing parameter values associated with each one of the continuously captured plurality of images; anddetermining breakthrough of substrate during the test process based on the pixel intensity values and parameter analysis.

8. The system of claim 1, further comprising a media mixer.

9. The system of claim 1, further comprising an uninterruptible power supply (UPS).

10. The system of claim 1, comprising the instructions executed to perform color calibration on each of the plurality of images prior to applying the binary threshold.

Images