Quantitative image analysis system for evaluating coating performance

Abstract

A system (100) for quantitative analysis of a coated substrate (35), comprising: an imaging system (10) for acquiring one or more images of the coated substrate, the imaging system being configured to acquire images of multiple channels, each of which channels includes a predetermined range of wavelengths; an illumination system (20) including at least one light source for illuminating the coated substrate; a holder (30) for holding the coated substrate in a position illuminated by at least one light source; and an analysis unit (40) configured to transform one or more images and quantitatively analyze one or more transformed images for defects in the coated substrate, wherein the coated substrate includes a coating formed on the surface of the substrate.

Description

Technical Field

[0001] The present invention generally relates to a quantitative image analysis system for evaluating the performance of coated substrates.

Background Art

[0002] The appearance of a coated substrate is one of the most important performance evaluation metrics used by consumers and researchers. Defects in a coated substrate can appear in many different ways, including color abnormalities, surface or texture differences, or other visible deviations. For example, the smoothness or leveling of a coated substrate may appear as a surface defect caused by a shadow or change in appearance. For example, resistance to defects caused by water, corrosion, dirt, grease, and weathering may appear as a change in the color of the coated substrate. Other defects within the coated substrate, such as movement / secretion or extraction of components within the coated substrate, may be more difficult to visually observe.

[0003] Such defects in a coated substrate are typically observed or measured by humans. Since it is difficult to evaluate many of the defects in a coated substrate, defect measurement is often difficult to accurately and / or reproducibly quantify. Most defect measurements are very subjective and are typically measured on a simple scale, such as a numerical scale of 1 to 5, and a human observer assigns a value based on their interpretation of the surface of the coated substrate. It is common for the values assigned by one observer to vary from the next, and defect quantification generally results in an approximation. For defects related to movement / secretion or extraction of components, these defects can be very difficult to see with the naked eye, making human observation and quantification even more difficult. Due to the subjective nature of the measurements, the observations are typically normalized in each study. Therefore, data obtained from human observations in one study cannot be reliably combined with data from another study.

[0004] Attempts have been made to automate the defect detection process. U.S. Patent Application Publication 2022 / 0082508 discloses a method for providing a coating composition-related prediction program, which includes providing a database of qualitative and / or quantitative characterizations of coating surfaces and training a machine learning model to develop a composition quality prediction program for predicting the properties of manufactured coating surfaces. However, the database of qualitative and / or quantitative characterizations is generated by manually identifying and labeling digital images, and the qualitative and / or quantitative characterization of the images is based on a scale with values ​​assigned by human observers. Thus, the database is compiled with data based on human observations.

[0005] To identify and quantify defects, a system is needed that can detect defects within coated substrates more accurately and reproducibly. [Overview of the project]

[0006] The present invention is a system for quantitative analysis of coated substrates, An imaging system for acquiring one or more images of a coated substrate, configured to acquire images of multiple channels, each of which includes a predetermined range of wavelengths, comprising: A lighting system including at least one light source for illuminating a coated substrate, A holder for holding a coated substrate in a position illuminated by at least one light source, Includes an analysis unit configured to convert one or more images and quantitatively analyze one or more converted images for defects in a coated substrate, The coated substrate relates to a system including a coating formed on the surface of a substrate. [Brief explanation of the drawing]

[0007] [Figure 1] This is a schematic diagram of a system for acquiring and analyzing images according to an embodiment of the present invention. [Figure 2]This is a schematic diagram showing the position of the light source relative to the coated substrate according to an embodiment of the present invention. [Figure 3] This is an image of an aneration test, analyzed by an image analysis system according to an embodiment of the present invention. [Figure 4] This is an image of an early rain resistance test, analyzed by an image analysis system according to an embodiment of the present invention. [Figure 5] This is an image of an adhesion test analyzed by an image analysis system according to an embodiment of the present invention. [Figure 6] This is an image from an applied opacity test, analyzed by an image analysis system according to an embodiment of the present invention. [Figure 7] This is an image of a stain resistance test, analyzed by an image analysis system according to an embodiment of the present invention. [Figure 8] This is an infrared image of a coated substrate used in a surfactant leaching test according to an embodiment of the present invention. [Figure 9] This is a visible light image of the coated substrate used in a surfactant leaching test according to an embodiment of the present invention. [Modes for carrying out the invention]

[0008] The inventors have found a method and system for reproducibly and accurately identifying and quantifying defects in coated substrates.

[0009] As used herein, the term “coated substrate” refers to a substrate having a coating on its surface, such as a paint coating on a metal or paper substrate. The coating preferably has a thickness of less than 500 μm, more preferably less than 300 μm, even more preferably less than 200 μm, and preferably greater than 50 nm, more preferably greater than 100 nm, and even more preferably greater than 250 nm. Multilayer coatings may have greater thicknesses. The coated substrate may include, for example, multiple layers including a primer or a base coat.

[0010] Preferably, the coated substrate includes a coating selected from polyurethane coating, epoxy coating, acrylic coating (e.g., acrylic coating, vinyl-acrylic coating, and styrene-acrylic coating), alkyd coating, and zinc-rich coating. More preferably, the coated substrate includes a paint. The substrate may include metal, plastic, wood, glass, composite material, glass fiber, paper, fabric, leather, or other substrates. For testing purposes, it is preferable that the substrate has a flat or planar surface.

[0011] Defects within or on coated substrates can be caused by a variety of issues. Examples of defects include, but are not limited to, color defects, surface or texture defects, and migration / secretion or extraction defects.

[0012] Color defects may include stains due to dirt, household stains (e.g., wine, pencil, lipstick, crayon, ink, marker, etc.), adhesion defects where the coating does not adhere sufficiently to the substrate, concealment defects where the coating allows the underlying substrate or sublayer to be visible, oil resistance which evaluates the penetration of oil through the coating, early rain resistance which tests the coating's ability to withstand runoff by rain immediately after application and curing, and efflorescence resistance which tests the coating's ability to withstand efflorescence and alkali burnout.

[0013] Texture or surface defects may be indicated by problems with smoothness or leveling, resulting in an irregular or imperfect surface of the coating. Other texture or surface problems may include, for example, cracking or delamination.

[0014] Migration / secretion and / or extraction occur when components separate from other components or migrate through the coating. Migration / secretion and / or extraction can result from incompatibility of materials in contact with the coating or components within the coating. For example, surfactant leaching can occur when the coating comes into contact with water, causing water-soluble materials to leach onto the surface of the coating. Other examples include the migration of binders or additives, which may be affected by time, temperature, or environmental conditions. Migration / secretion and / or extraction can result in visible defects, although often such defects are not readily apparent. However, the inventors have surprisingly found that migration / secretion and / or extraction defects can be identified and analyzed using infrared and / or ultraviolet spectra. Species that may migrate / secrete or be extracted may have different properties observable in infrared and / or ultraviolet spectra. For example, when analyzing surfactant leaching, the inventors have found that migrating components have different thermal conductivity than the remaining components, making these defects readily identifiable in infrared spectra.

[0015] A system for analyzing and quantifying defects is provided for analyzing coated substrates. A schematic diagram of the defect analysis and quantification system 100 is shown in Figure 1. The system 100 includes an imaging system 10, an illumination system 20, a holder 30 for holding the coated substrate 35, and an analysis unit 40.

[0016] The imaging system 10 is configured to acquire one or more images of the coated substrate 35. The imaging system 10 is configured to acquire images of multiple channels, each of which contains wavelengths within a predetermined range. For example, each channel may consist of wavelengths associated with a single color of light in the visible spectrum (e.g., red = 620-780 nm, orange = 585-620 nm, etc.). Alternatively, each channel may consist of wavelengths within a predetermined range (e.g., channel 1 = 400-500 nm, channel 2 = 500-600 nm, etc.). In yet another example, one channel may contain the visible light spectrum, and the second channel may contain either the ultraviolet spectrum or the infrared spectrum. In yet another example, one channel may contain wavelengths in the near-infrared range (800-1000 nm), and the second channel may contain longer infrared wavelengths (e.g., 1000-1500 nm). Preferably, the imaging system is configured to acquire images in at least one channel containing wavelengths in the visible light spectrum and at least one channel containing wavelengths in the infrared spectrum, the ultraviolet spectrum, or both. More preferably, the imaging system is configured to acquire images in at least one channel containing wavelengths in the visible light spectrum and at least one channel containing wavelengths in the infrared spectrum. In embodiments where the system is used to detect migration / secretion and / or extraction defects, the imaging system 10 is configured to acquire images in the infrared spectrum, the ultraviolet spectrum, or both.

[0017] In embodiments where the defects being analyzed are color-based defects, the imaging system may be configured to acquire an image in the channel most relevant to the color of the defect. For example, when analyzing a coated substrate for early rain resistance testing, the substrate may be provided with a blue primer and then coated with a white paint. When exposed to water, the defects expose the underlying blue primer. The imaging system 10 may then be configured to acquire at least one image in a channel containing blue wavelengths. A second channel may be used as a control.

[0018] The imaging system 10 may include, for example, a camera, a thermal imaging system, an ultraviolet imaging system, or an image sensor. The imaging system 10 may further include filters for preferentially or selectively transmitting or blocking light of a predetermined wavelength, such as one or more channels of a predetermined wavelength. For example, if the imaging system 10 is configured to detect in the ultraviolet spectrum, a filter can be used to block a channel of visible light. Alternatively, if ultraviolet light is used to induce fluorescence in a particular component, a filter may be used to selectively transmit fluorescence wavelengths, and the imaging system may be configured to acquire an image in a channel containing fluorescence wavelengths. Similarly, if the infrared spectrum is used, a filter can be used to block visible wavelengths and allow transmission of infrared wavelengths.

[0019] Illumination system 20 includes at least one light source for illuminating the coated substrate 35. The illumination system 20 may be configured to emit radiation in the visible spectrum, infrared spectrum, ultraviolet spectrum, and combinations thereof. Preferably, the illumination system is configured to emit radiation at wavelengths associated with at least one of the plurality of channels used by the imaging system 10. For example, when detecting movement and / or secretion defects, the illumination system 20 may be configured to emit radiation in the infrared and / or ultraviolet spectrum, and the imaging system may be configured to acquire images at the same wavelength. The at least one light source may include a single light source or a plurality of light sources. When using a single light source, the light source may include a ring light or a diffuser to provide uniform illumination to the coated substrate 35. When a plurality of light sources are used, the light sources may be arranged to provide uniform illumination. The plurality of light sources may also be controlled individually or within a predetermined group to control the illumination of the coated substrate 35. Preferably, the illumination system 20 is configured to allow adjustment of the intensity of the light, the angle of incidence on the coated substrate 35, or the wavelength of the emitted light. To reduce potential effects from external illumination, the system 100 may be covered or surrounded such that only light from the illumination system 20 is used to acquire images (not shown).

[0020] Substrate holder 30 is used to hold the coated substrate 35 for imaging by the imaging system 10. The holder 30 is configured to hold the coated substrate in a position where it is illuminated by the illumination system 20 when it is imaged. The holder 30 may be configured to hold a single coated substrate 35 or a plurality of coated substrates. The holder 30 may be stationary or adapted to automatically load / unload test specimens.

[0021] Preferably, one or more of the imaging system 10 and the holder 30 are adjustable such that the position of the coated substrate 35 can be changed with respect to the imaging system 10. For example, as shown in FIG. 1, the imaging system 10 may be mounted on an arm 101 attached to a vertical support 102. The arm 101 may be configured to be adjustable so as to be able to select the distance between the imaging system 10 and the holder 30. Alternatively, the arm 101 may be movable between two or more positions. In another alternative, the holder 30 may be adjustable to raise or lower the holder 30 using a base 103, or the angle of the holder with respect to a fixed position may be adjusted.

[0022] Preferably, one or more of the illumination system 20 and the holder 30 are adjustable such that the position of the coated substrate 35 can be changed with respect to the illumination system 20. For example, as shown in FIG. 2, the illumination system 20 may be adjustable in height or angle with respect to the holder 30 to vary the incident angle α of the light 25. For example, the illumination system 20 may be adjustable to allow a shallower or steeper incident angle onto the coated substrate 35. Further, the illumination system 20 may be adjustable to allow rotation of the illumination system 20 around the coated substrate 35 such that the incident angle α is the same but the light is directed from a different angle, for example, from the side rather than the front of the coated substrate 35.

[0023] System 100 further includes an analysis unit 40 configured to transform images acquired by the imaging system 10. The analysis unit 40 further quantitatively analyzes the transformed images to identify and / or quantify the amount or percentage of defects within or on the coating of the coated substrate 35. The analysis unit 40 may include, for example, a computer, workstation, notebook computer, tablet computer, or smartphone. The analysis unit 40 may include an application or program adapted to transform and analyze images from the imaging system 10. The information acquired and / or generated by System 100 may be stored locally in the analysis unit 40, a server, cloud storage, or a media storage device.

[0024] The analysis unit 40 is preferably configured to transform the acquired image by processing the acquired image using an algorithm selected from image thresholding, wavelet transform, morphological transformation, color detection, pattern detection, contrast detection, clustering, and combinations thereof. The transformed image is then analyzed by the analysis unit 40 to identify and / or quantify defects within or on the coating of the coated substrate 35 and may provide an analysis output. Preferably, the output includes a value indicating the amount / percentage of defects, and / or an image or dataset identifying the location, size and / or amount / percentage of defects.

[0025] Preferably, the analysis unit 40 includes or is connected to a display including a graphical user interface (GUI). The GUI is preferably configured to display the output of the analysis unit 40. For example, the GUI may display a value that quantifies the amount or percentage of defects present in the coated substrate 35. Alternatively, the GUI may display a converted image that identifies the location, size, and / or number / percentage of defects.

[0026] The method for identifying and quantifying defects in a coated substrate according to the present invention includes providing a system for acquiring and analyzing images; loading a substrate into a holder; illuminating the coated substrate using an illumination system; acquiring one or more images of the coated substrate using an imaging system; converting one or more images of the coated substrate using an analysis unit to provide one or more converted images; identifying and quantifying defects in the coated substrate based on one or more converted images; and providing an output.

[0027] Illuminating a coated substrate using an illumination system to identify and quantify defects based on the migration / secretion and / or extraction of one or more components within the coating of the coated substrate includes illuminating the coated substrate with infrared, ultraviolet, or both types of radiation. The image acquired by the imaging system includes infrared and / or ultraviolet images. Migration / secretion and / or extraction can be determined by the transformed image, which shows regions with different absorbances or reflectances at different wavelengths in the infrared and / or ultraviolet spectrum based on the migrating / secreted or extracted components. [Examples]

[0028] A system with a configuration similar to that shown in Figure 1 was prepared using a 5MP camera as the imaging system, an 8-channel multispectral light ring as the illumination system, and a customizable specimen holder for holding coated substrates for imaging and analysis. The 8-channel multispectral light ring was configured to emit channels consisting of ultraviolet, blue, green, yellow, red, far-red, infrared, and white light. The camera was configured to have the ability to acquire images in each of the channels emitted by the illumination system.

[0029] Next, all or a subset of the acquired images were transformed using the image analysis algorithm t. The image analysis algorithm identified and quantified defects on the coated surface.

[0030] Ephemeralization test (predictive example) To test the efflorescence resistance of the primer, a coated substrate is prepared by covering it with the primer and topcoat. The bottom of the coated substrate is brought into contact with an alkaline liquid to determine whether the primer can block the penetration of the alkaline liquid.

[0031] The sample is analyzed by human observation and by the system of the present invention. A representative image of the analysis is shown in Figure 3, where bright areas are expected to indicate corrosive areas, i.e., areas where the coating cannot block the movement of the alkaline solution, and dark areas are expected to indicate non-corrosive areas, i.e., areas where the coating is effective. Human observation is performed by estimating the areas where color changes can be observed. Analysis by the system of the present invention is expected to be quantifiable and reproducible.

[0032] Early rain resistance test (predictive example) To test the water resistance of a wet coating that has been cured for 20 minutes, a substrate coated with a blue primer is coated with a white topcoat. The topcoat is allowed to cure for 20 minutes, and then water is applied to the top of the coated substrate for a predetermined time. As the water washes over the coated substrate, it is expected that a portion of the white topcoat will peel off, revealing the blue primer underneath. Figure 4 shows an image of the coated substrate after a similar water resistance test.

[0033] Next, the sample is analyzed by humans and by the system of the present invention. Human observation is for estimating the amount or proportion of blue visible through the white topcoat. The sample is also analyzed by the system of the present invention, which is expected to provide reproducible and quantifiable results.

[0034] Adhesion test A paint sample was applied to a substrate and cured. A set of lines was engraved using a cross-hatch tool. Tape was applied and pulled from the cross-hatched area. The adhesive strength of the paint was quantified by a human tester who counted the number of grids in which paint remained in the cross-hatched area. An image of the sample (Figure 5) was also analyzed using the system of the present invention using frequency space to identify areas and quantify the percentage of residual paint.

[0035] The system of the present invention was also able to quantify the adhesion of the clear coat based on the light profile used. The clear coat was difficult for human testers to observe accurately and reproducibly.

[0036] Application Concealment Test Paint samples were applied at a natural diffusion rate onto a Leneta chart, i.e., a chart having a combination of black and white areas. After the paint dried, the covered chart was analyzed by a human tester, who evaluated it on a scale of 1 to 5 based on how much of the underlying black area was observable. Images of the same samples (Figure 6) were analyzed using the system of the present invention, which used wavelet transform to identify areas and quantified the opacity by constructing a linear regression between pixel intensity and manual evaluation. The analysis using the system of the present invention was more quantitative and reproducible compared to human observation.

[0037] Stain resistance test The stain resistance test was first performed by applying selected stains to the painted substrate. Possible stain types included common household stains such as pencil, wine, crayon, coffee, fine and thick marker stains, and dirt. The samples were then washed or scrubbed with a sponge for a specified number of cycles. The stain resistance of the paint was then quantified using the color change before and after washing. Figure 7 shows images of painted substrates stained with various materials, including markers, pencils, and crayons.

[0038] Surfactant leaching test To test surfactant leaching, the paint was applied to a substrate and dried in a constant temperature and humidity chamber for 4 hours. The coated substrate was placed horizontally on a stand, and water was poured onto three separate areas of the paint. After a certain period, the coated substrate was suspended vertically to allow the water to drain off. The sample was dried, and then the coated substrate was analyzed.

[0039] The coated substrate was placed on a holder within a system for analyzing the coating. The surface of the coated substrate was illuminated using a light source emitting infrared light, and infrared images were acquired using a camera, as shown in Figure 8. Visible light images were also acquired, as shown in Figure 9. As can be seen by comparing Figures 8 and 9, no trails were visible in the visible light images, but clear trails were visible in the infrared images. The acquired infrared images were analyzed using a computer that applied a contrast detection algorithm to maximize the contrast in the images. The algorithm further calculated the total contrast in areas showing surfactant leaching, providing a value to quantify the amount of leaching present on the surface of the coated substrate.

[0040] For comparison, the same samples were analyzed by human observation to estimate the amount of leaching. The amount of defects was evaluated on a scale of 1 to 5.

Claims

1. A system for quantitative analysis of coated substrates, An imaging system for acquiring one or more images of the coated substrate, configured to acquire images of multiple channels, each of which includes a predetermined range of wavelengths, comprising: A lighting system including at least one light source for illuminating the coated substrate, A holder for holding the coated substrate in a position illuminated by at least one of the aforementioned light sources, Includes an analysis unit configured to convert one or more images and quantitatively analyze the one or more converted images for defects in the coated substrate, The coated substrate is a system including a coating formed on the surface of the substrate.

2. The system according to claim 1, wherein the plurality of channels include channels in at least two spectra selected from the visible light spectrum, the infrared spectrum, and the ultraviolet spectrum.

3. The imaging system according to claim 2, wherein the imaging system is configured to acquire at least one visible light image in a channel in the visible light spectrum and at least one infrared image in a channel in the infrared spectrum.

4. The system according to claim 3, wherein the analysis unit is configured to convert the at least one visible light image and the at least one infrared image, and the analysis unit is further configured to quantitatively analyze the defects in the coated substrate by comparing defects in the at least one visible light image with defects in the at least one infrared image.

5. The system according to claim 4, wherein comparing defects in the at least one visible light image with defects in the at least one infrared image includes identifying the maximum amount of defects detected in the at least one visible light image and the at least one infrared image.

6. The system according to any one of claims 1 to 5, wherein at least one of the imaging system and the holder is adjustable to change at least one parameter selected from the angle between the imaging system and the holder, the distance between the imaging system and the holder, and the relative position between the imaging system and the holder.

7. The system according to any one of claims 1 to 6, wherein at least one of the lighting system and the holder is adjustable to change at least one parameter selected from the angle between the lighting system and the holder, the distance between the lighting system and the holder, and the relative position between the lighting system and the holder.

8. The system according to any one of claims 1 to 7, wherein the at least one light source includes a plurality of light sources.

9. The system according to any one of claims 1 to 7, wherein the at least one light source includes a ring light or a diffuse light source.

10. The system according to any one of claims 1 to 9, wherein the at least one light source emits light from at least one spectrum selected from the visible light spectrum, the infrared spectrum, the ultraviolet spectrum, and combinations thereof.

11. The imaging system further includes at least one filter, the at least one filter that preferentially transmits light of one wavelength among the plurality of channels, or preferentially blocks light of one wavelength among the plurality of channels, according to any one of claims 1 to 10.

12. The system according to any one of claims 1 to 11, wherein transforming one or more images includes applying at least one transformation selected from image thresholding, wavelet transform, morphological transformation, color detection, pattern detection, clustering, and combinations thereof.

13. The system according to any one of claims 1 to 12, further comprising a graphical user interface (GUI) for displaying one or more converted images and for displaying a quantification of the defects in the coated substrate.

14. The system according to claim 13, wherein the GUI is configured to select one or more of the plurality of channels for acquiring one or more images and to select the type of defect to be analyzed by the analysis unit.

15. The system according to any one of claims 1 to 14, wherein the coating includes a paint.

Images