Systems, methods, and interfaces for comparing complex coating mixtures with flash color

Abstract

A computer system for comparing complex coating mixtures with flash colors can receive at least one image of a target coating. The computer system calculates a flash color distribution of the at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color to the number of flash points of one or more other colors in a measured region. Furthermore, the computer system searches a database for a plurality of reference coatings having flash color distributions that match the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution. The computer system calculates the degree to which the plurality of reference coatings match the target coating based on the flash color distributions. Finally, the computer system identifies the closest matching reference coating from the plurality of reference coatings.

Description

[0001] Cross-reference to related applications

[0002] This application claims the benefit and priority of U.S. Provisional Patent Application No. 63 / 155,569, filed March 2, 2021, entitled “Systems, methods, and interfaces for comparing complex coating mixtures with sparkle color,” which is expressly incorporated herein by reference in its entirety. Background Technology

[0003] Modern coatings serve several important functions in industry and society. Coatings protect the coated material from corrosion, such as rust. They also provide aesthetic benefits by giving objects specific colors and / or textures. For example, most automobiles are coated with paint and various other coatings to protect the car's metal body from the elements and to provide an attractive visual effect.

[0004] Given the wide range of applications for different coatings, it is often necessary to identify the target coating composition. For example, it might be necessary to identify the target coating composition on a car that has been in an accident. However, due to the complex nature of the mixtures within coatings, it can sometimes be difficult to formulate, identify, and / or search for acceptable matching formulations and / or pigment deposits. In an ideal environment, an individual could examine the complex coating mixtures and determine the appropriate pigments within them. In reality, the pigments in a coating mixture may not be readily available in the set of toners used to create the matching coating. Therefore, a skilled colorist must determine whether the paint system contains an appropriate offset, and if so, must determine the additional modifications needed to accommodate the offset, provided that the offset does not perfectly match the original pigment deposits.

[0005] A hypothetical solution for determining the composition of an unknown pigment deposit is to read the unknown pigment deposit using a device that can search a database for the best-matching coating formulation (or a device that can immediately generate a new coating formulation). However, this solution is only hypothetical, because while the system can determine the color or bulk effect pigment type, it typically cannot help determine, for example, the specific microparticles required for coating formulation matching.

[0006] Therefore, there are many opportunities for new methods and systems to improve coating identification. When a vehicle is being repaired, the touch-up paint applied to the vehicle should match the original paint. Summary of the Invention

[0007] The systems, methods, and computer program products described herein can provide significant improvements to coating formulation methods. For example, the present invention includes a system for comparing complex coating mixtures with shimmering colors. The present invention also includes computer-implemented methods and related computer program products for comparing complex coating mixtures with shimmering colors. Therefore, the computer systems and methods disclosed herein can provide a solution that identifies special effect pigments and generalizes the ratios of those pigments, thus achieving faster and better color matching while providing higher quality color matching.

[0008] For example, a computer system for comparing complex coating mixtures with flash colors can be configured to receive at least one image of a target coating. The computer system can also calculate the flash color distribution of the at least one image of the target coating, where the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors. Furthermore, the computer system can search a database for multiple reference coatings with flash color distributions that match the target coating, where each of the multiple reference coatings has a different flash color distribution. The computer system can calculate the degree to which the multiple reference coatings match the target coating based on the flash color distribution. Additionally, the computer system can identify the closest matching reference coating from the multiple reference coatings.

[0009] Additionally, a computerized method for comparing complex coating mixtures with flash colors may include receiving at least one image of a target coating. Furthermore, the method may include calculating a flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in a measured region compared to the number of flash points of one or more other colors. The method may further include searching a database for a plurality of reference coatings having flash color distributions that match the target coating, wherein each of the plurality of reference coatings has a different flash color distribution. The method may include calculating the degree to which the plurality of reference coatings match the target coating based on the flash color distributions. Furthermore, the method may include generating a list of the plurality of reference coatings with the closest matching flash color distributions compared to the flash color distribution of the target coating.

[0010] Furthermore, another computerized method for comparing complex coating mixtures with flash colors may include calculating the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured region compared to the number of flash points of one or more other colors. The method may also include searching a database for multiple reference coatings with flash color distributions that match the target coating. Additionally, the method may include using z-score analysis based on the flash color distribution to calculate the degree to which the multiple reference coatings match the target coating. Furthermore, the method may include generating a list of the multiple reference coatings with the closest matching flash color distributions compared to the flash color distribution of the target coating.

[0011] Additional features and advantages will be set forth in the following description, and in part will be obvious from the description or may be learned by practice. These features and advantages can be realized and obtained by the instruments and combinations particularly pointed out in the appended claims and aspects. These and other features will become more apparent from the following description and the appended claims, or may be learned by practice of the examples set forth below. Attached Figure Description

[0012] To illustrate how the above and other advantages and features can be obtained, a more specific description of the above brief description will be presented by reference to specific examples of the invention, illustrated in the accompanying drawings. It should be understood that these drawings are illustrative only and are therefore not intended to limit its scope. A computer system for dynamically resolving digital images to identify coating colors will be described and explained with additional specificity and detail using the accompanying drawings, in which:

[0013] Figure 1 A schematic diagram of a computerized system for comparing complex coating mixtures with shimmering colors, according to an embodiment of the present invention, is shown.

[0014] Figure 2 An example of an image in which the flash color has been indicated by circles;

[0015] Figure 3A A diagram showing an exemplary flash color distribution;

[0016] Figure 3B Another diagram showing an exemplary flash color distribution;

[0017] Figure 3C Another diagram showing an exemplary flash color distribution;

[0018] Figure 3D The graph shows the relationship between color and z-score;

[0019] Figure 4A schematic diagram of a graphical user interface depicting a list of the closest matching reference coating flash color distributions;

[0020] Figure 5 A flowchart depicting the steps within a method for comparing complex coating mixtures with shimmering colors; and

[0021] Figure 6 A flowchart depicting the steps within an alternative method for comparing complex mixtures with shimmering colors. Detailed Implementation

[0022] The systems, methods, and computer program products described herein can provide significant improvements to coating formulation methods. For example, the present invention includes a system for comparing complex coating mixtures with shimmering colors. The present invention also includes computer-implemented methods and related computer program products for comparing complex coating mixtures with shimmering colors. Therefore, the computer systems and methods disclosed herein can provide a solution that identifies special effect pigments and generalizes the ratios of those pigments, thus achieving faster and better color matching while providing higher quality color matching.

[0023] For example, a computer system for comparing complex coating mixtures with flash colors can be configured to receive at least one image of a target coating. As used herein, a target coating includes any coating of interest that has been applied to any physical object. The computer system can also calculate the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors. Furthermore, the computer system can search a database for multiple reference coatings with flash color distributions that match the target coating, wherein each of the multiple reference coatings has a different flash color distribution. The computer system can calculate the degree to which the multiple reference coatings match the target coating based on the flash color distributions. Additionally, the computer system can identify the closest matching reference coating from the multiple reference coatings.

[0024] Those skilled in the art will understand that automotive coatings present a particularly challenging set of coating parameters to match. In addition to complex colorants (such as pigments, dyes, and inks), conventional automotive coatings may also include effect pigments, such as those that provide texture to the coating. For example, automotive coatings may include effect pigments, such as aluminum flakes of a specific color. Aluminum flakes can provide a texture that appears "shimmering."

[0025] Generally, while the term "flash" is understood by those skilled in the art in the field of coatings and related technologies, it should be understood to refer to small, specific bright spots, glitter points, or sparkles in a particular area of ​​the coating. According to ASTM E284, "flash" refers to an aspect of the appearance of a material that appears to emit or reveal tiny bright spots that are strikingly brighter than their immediate surroundings and become more apparent when at least one of the contributing factors (observer, sample, light source) is moved. Furthermore, flashes can be classified into flash grades (S...). g ), flash intensity (S) i ) and flashing area (S a The "flash area" is a segment of the illuminated surface of an object where a spot is strikingly brighter than its immediate surroundings. In contrast, "flash intensity" is the contrast between the visible bright spots on the grains of an angle-dependent pigment and their immediate surroundings. Parameter S i It is the sum of the recording intensities of all individual pigments, and Sg is defined as S i and S a The geometric mean is as follows:

[0026]

[0027] While a coating can provide general brightness or brilliance at different points and angles through the combined effect of all materials in the coating, a flash is a more specific point of light or brilliance provided by a relatively small sub-component of the coating (such as a particular aluminum flake, mica flake, or other element). Therefore, proper identification of such coating compositions may require correctly identifying the presence of the flash-generating component, such as the amount, type, and distribution of the aluminum flake, as well as the appropriate identification of the color of the aluminum flake.

[0028] Traditional techniques for evaluating the properties of complex coating mixtures involve the use of spectrophotometers (e.g., in-plane multi-angle apparatus for effect samples and spherical apparatus for direct-negative samples). However, new pigments are often difficult to characterize adequately using such techniques due to the unique properties of effect materials (e.g., COLORSTREAM (manufactured by MERCK) particles, colored aluminum, etc.). For example, examining COLORSTREAM pigments can be challenging, and it may be nearly impossible to observe the roughness of colored aluminum. Therefore, in such cases, microscopy may be necessary to adequately characterize the special effect pigment. The use of microscopy or other instruments can be a time-consuming process and may not satisfactorily address the application of modified sample properties and the effects of special pigments.

[0029] In some cases, human experts aid in identifying colorants within a coating by making informed guesses about the specific colorants that might be present in it. The downside is that even experts with extensive color-matching experience may struggle to guess the colorant composition in complex coatings. This inaccuracy may be at least partly due to the expert being limited to visual matching from a library of hundreds or thousands of colorant combinations that could be present in any given coating.

[0030] Compared to conventional methods, the systems and methods described herein utilize statistical comparisons of flash color distributions between images (i.e., photographic images) to find similar coating colors. Such systems offer significant technical improvements over conventional coating formulation methods. For example, at least one system or method described herein can provide accuracy without requiring a spectrophotometer or microscope to fully characterize the target coating. In particular, embodiments of the systems and / or methods may employ a basic camera capable of substantial magnification to capture images of the target coating. Furthermore, because the systems and methods described herein compare the captured image data with known image data, in at least one described system or method, the systems and methods of the present invention can identify similar coating colors using only one image taken from a single angle, thus providing a significant advantage.

[0031] Therefore, the computer systems and methods disclosed and claimed herein provide a solution for rapidly identifying special effect pigments and generalizing the ratios of those pigments, thus achieving faster and better color matching while providing higher quality color matching. Furthermore, the coating comparison process disclosed herein can detect subtle color changes that are imperceptible to the human eye. In addition, the described computer system can improve the speed at which automotive body repair shops can identify touch-up paint colors, thereby increasing their productivity.

[0032] Now turn to the attached diagram. Figure 1 A schematic diagram of a computerized system according to an embodiment of the present invention is shown, the computerized system including a computer system 100 for comparing complex coating mixtures having shimmering colors. About Figure 1 The computer system 100 is described in the exemplary context of recognizing texture effects (e.g., aluminum, organic mica, or synthetic mica); however, it will be understood that the computer system 100 may additionally or alternatively be used to recognize any type of colorant, effect component (or flake), etc. Those skilled in the art will understand that the depicted schematic diagrams are merely exemplary, and although the computer system 100 is described in the exemplary context of recognizing texture effects (e.g., aluminum, organic mica, or synthetic mica), it is not intended to be a definitive representation of texture effects. Figure 1 While described as a desktop computer, the computer system 100 can take many forms. For example, the computer system 100 can be a laptop computer, tablet computer, wearable device, mobile phone, mainframe, etc.

[0033] As used herein, a computer system used in conjunction with the present invention includes any combination of one or more processors 110(ac) and computer-readable storage media (not shown). For example, a processor (e.g., “first processor” 110a) may include an integrated circuit, a field-programmable gate array (FPGA), a microcontroller, analog circuitry, or any other electronic circuitry capable of processing input signals. Examples of computer-readable storage media include RAM, ROM, EEPROM, solid-state drives (“SSDs”), flash memory, phase-change memory (“PCM”), optical disc storage devices, magnetic disk storage devices, or other magnetic storage devices, or any other hardware storage device. Computer system 100 may be distributed across a network environment and may comprise multiple constituent computer systems.

[0034] Computer system 100 may include one or more computer-readable storage media thereon storing executable instructions that, when executed by one or more processors 110(ac), configure computer system 100 to execute coating analysis software application 105. Coating analysis may include calculating the degree to which multiple reference coatings match target coating 130 based on the distribution of flash colors within target coating 130.

[0035] For example, coating analysis software application 105 enables computer system 100 to receive at least one image 135 of target coating 130. Image 135 may be, for example, captured by camera 125 (e.g., ...). Figure 1 The image 135 of the target coating 130 is captured by a spectrophotometer, smartphone, microscope, or any other device capable of scanning the target coating 130 and providing characteristic data related to the photographic / image properties of the target coating 130. Alternatively or additionally, the image 135 of the target coating 130 includes RGB values ​​from pixel image data. Image 135 may contain associated metadata containing information about camera settings (e.g., magnification, illumination, resolution, camera angle, etc.). For the purposes of this specification and claims, the term "pixel" means the smallest element of an image that can be processed in a video display system and includes at least the following information: (i) address (e.g., X / Y position data); and (ii) color value and / or light value (e.g., RGB, γ-RGB, colorimetric, and / or correlated values). In contrast, a "pixel cluster" includes values ​​associated with a group of two or more pixels, wherein the grouping is described by an average, mean, or other form of statistical modeling. Thus, "flash color" as used herein may include a single pixel value or a value associated with a pixel cluster.

[0036] like Figure 1As shown herein, the coating analysis software application 105 may include various modules, such as an image processing module 140, an input / output (I / O) interface 145, and a mixing engine 150. As used herein, modules may include software components (containing software objects), hardware components (e.g., discrete circuits, FPGAs, computer processors), or some combination of hardware and software. However, it will be understood that separating modules into discrete units is at least to some extent arbitrary, and modules may be excluded from... Figure 1 The computer system can combine, associate, or separate components in ways other than those shown in the diagram, while still achieving its intended purpose. Therefore, Figure 1 Modules 140, 145 and 150 are shown for illustrative and exemplary purposes only.

[0037] The coating analysis software application 105 can also communicate with one or more databases, such as Figure 1 As shown in the illustration. For example, the coating analysis software application 105 may communicate with the coating color database 120. As used herein, the database may include locally stored data, remotely stored data, data stored within an organized data structure, data stored within a file system, or any other stored data accessible to the coating analysis software application 105.

[0038] like Figure 1 As shown, the image processing module 140 of the coating analysis software application 105 is configured to receive an image 135 of the target coating 130 and subsequently determine the flash color distribution 300 of the image 135 of the target coating 130 (see [reference]). Figure 3A The image processing module 140 can sharpen an image 135 (or at least a portion of the image 135) of the target coating 130, isolate high-intensity pixels to identify flash points, and perform hue analysis to determine the flash color of the flash points, thereby calculating the flash color distribution 300.

[0039] For example, Figure 2 The image 200 is shown as "flash-only" (meaning that image processing module 140 sharpens and isolates high-intensity pixels in at least a portion of image 135), which demonstrates a simplified selection. Specifically, Figure 2 An image of five distinct points of brilliance is shown for illustrative purposes. The image processing module 140 is configurable to analyze each of these brilliance points to determine their hue. Figure 2 In the image, the five flashing dots can contain at least one blue, one purple, one green, one red, and one orange flashing color.

[0040] like Figure 3AAs shown, data from the analyzed flash points can be used to calculate the flash color distribution 300, which represents the relative number of flash points of one color in the analyzed portion of image 135 compared to the number of flash points of one or more other colors. Figure 3A The flash color distribution 300 shown in the image lists the identified colors on the x-axis and the pixel count for each identified color on the y-axis. Although Figure 3A The flash color distribution 300 is displayed graphically, but the coating analysis software application 105 may additionally or alternatively store the data numerically. Those skilled in the art will understand that... Figure 3A The colors and pixel counts shown are for illustrative purposes only. They correspond to Tables I and II. Figures 3B to 3C Further plots are provided showing the pixel counts relative to the listed colors for various target samples.

[0041] Refer again Figure 1 Once the image processing module 140 calculates the flash color distribution 300, it can search the coating color database 120 for a reference coating with a flash color distribution that matches the flash color distribution 300 of the target coating 130. The coating color database 120 may contain numerical data of the flash color distribution of known coating formulations. The coating color database 120 may also contain other metadata associated with the flash color distribution data of each known coating formulation. For example, the metadata may contain information about the camera settings (e.g., magnification, illumination, resolution, camera angle, etc.) of the image used to calculate the flash color distribution data of the coating formulation.

[0042] Image processing module 140 can be configured to compare the flash color distribution 300 of image (135) with flash color distribution data captured from images having similar associated metadata within coating color database 120. For example, if image 135 is captured at a first angle, image processing module 140 can search in coating color database 120 for a reference coating having a flash color distribution from an image also captured from the first angle. Alternatively, if a specific camera magnification is used to capture a target coating 130 in image 135, image processing module 140 can search in coating color database 120 for a reference coating having a flash color distribution from an image including the same camera magnification.

[0043] In at least one method described herein, at least one additional image of the target coating 130 is captured from at least one additional angle. The image processing module 140 can calculate a flash color distribution based on the additional image of the target coating 130 at the additional angle. The image processing module 140 can be configured to use both the flash color distribution of the target coating 130 at a first angle and the flash color distribution of the target coating 130 at the additional angle to search for similar coating references in a database.

[0044] Figure 1 The image processing module 140 shown herein can also be configured to identify the “inverted flash color” of the image 135 of the target coating 130. As used herein, “inverted flash color” refers to the background color, that is, the color of the panel that is separate from the color of the flash itself. The inverted flash color can be identified by isolating high-intensity pixels in (or at least a portion of) the image 135 and deselecting the isolated high-intensity pixels. The image processing module 140 can search the coating color database 120 based on the inverted flash color of a reference coating that matches the target coating 130. To narrow down the search results, the image processing module 140 can first use the inverted flash color to search the coating color database 120 for matching the reference coating before using the calculated flash color distribution 300 for searching.

[0045] Image processing module 140 then calculates the degree to which the reference coating matches the target coating 130 by statistically comparing the glitter color distribution of the reference coating. z-score analysis provides an opportunity to make quantitative decisions about the arrangement of glitter effect pigments between the target coating and the analyzed reference coating. Alternatively, z-score analysis can provide an additional test metric for search methods, where panels containing similar effects are found even when the overall appearance is outside the visual tolerance. In one embodiment, image processing module 140 can use z-score analysis to compare each color within the glitter color distribution 300 of image 135 with the corresponding color in the glitter color distribution of the reference coating to assign a z-score to each color. The following z-score formula can be used, which compares two proportions rather than absolute values:

[0046]

[0047] Where z is the z-score. The proportion of individual color pixels in the first coating to the total number of pixels of all colors. The proportion of individual color pixels in the second coating relative to the total number of pixels of all colors. Let n1 be the proportion of individual color pixels in the two coatings to the total number of pixels in the two coatings, and n2 be the total number of pixels in the first coating and n2 be the total number of pixels in the second coating.

[0048] The acceptability threshold for each color comparison can be set by the user. The z-score threshold can remain constant or the user can change the threshold according to the quality of the pixel image data. Based on z-score analysis, the image processing module 140 can identify the degree to which the target coating 130 matches the analyzed reference coating. If the z-score of at least one analyzed color falls outside the z-score threshold, then the image processing module 140 can determine that the target coating and the analyzed reference coating are likely significantly different. The degree of matching can be expressed as a percentage. For example, Figure 3D Table III shows the plot of color matching and z-scores. Figure 3D The table shows a wide range of color matches within the "Different" category, implying that the color matching is imprecise. In contrast, Table III shows a graph of more precise color matches on the right, as can be seen from the much closer range of z-scores.

[0049] Compared to conventional analytical methods, at least one embodiment of the present invention provides the use of a relatively wide threshold to determine a match. While this may result in a low match rating between the actual observed colors (i.e., inverted glitter colors) of the target sample / background, a wide z-score value can simultaneously identify a subcomponent composition with at least similar colors but closer to a match, as well as a reference coating with its concentration. In other words, the z-score can be essentially set to focus on non-glitter-specific aspects and then allow for subsequent fine-tuning of the color values. For example, if the target coating 130 includes a red inverted glitter color, and the analyzed target coating includes an inverted glitter color that does not match the inverted glitter color of the target coating 130 (e.g., another red or white shade), then the image processing module 140 can be configured to allow the z-score of at least one of the analyzed colors to exceed the threshold. Thus, the image processing module can calculate the degree to which the glitter effect pigment of the reference coating matches the glitter effect pigment of the target coating 130.

[0050] Image processing module 140 can generate a list 400 of the closest matching flash color distributions of the reference coating compared to the flash color distribution 300 of the target coating 130. Figure 4 (As shown in the image). Furthermore, the image processing module 140 can use the closest matching flash color distribution to select the closest matching reference coating.

[0051] like Figure 1 As shown, once the computer system 100 has generated a list 400 of the closest matching flash color distributions of multiple reference coatings, the coating analysis software application 105 within the computer system 100 can provide the list 400 to the end user via the input / output (I / O) interface 145. The I / O interface 145 allows the computer to access the graphical user interface 155 (...). Figure 4 The list shown is 400.

[0052] like Figure 4 As shown, the graphical user interface 155 can list reference coatings in order of highest probability. List 400 may include names 410a to 410e and images 420a to 420e for each reference coating, allowing the user to visually compare the depicted colorant image with the target coating 130. Additionally, the graphical user interface 155 can display the calculated correlation percentages 430a to 430e.

[0053] like Figure 1 As shown, the mixing engine 150 can communicate with both the image processing module 140 and the I / O interface 145. The mixing engine 150 can generate coating adjustment mixtures to adjust the closest matching reference coating into the target coating. The coating adjustment mixtures can also generate a list of toners. The mixing engine 150 can be configurable to send the coating adjustment mixtures to the I / O interface 145. The I / O interface 145 can then display the coating adjustment mixtures to an end user and / or transmit the coating adjustment mixtures to a coating mixer communicating with a computer system for production.

[0054] In at least some of the systems and methods described herein, the flash color distribution 300 of image 135 can be compared with the flash color distribution of a reference coating within coating color database 120 without filtering based on the inverted flash color. Therefore, a coating adjustment formulation may involve changing the inverted flash color of the closest matching reference coating. For example, if the target coating 130 includes a red inverted flash color and the closest matching reference coating includes a white inverted flash color, then the coating adjustment formulation may involve changing the inverted flash color of the closest matching reference coating from white to red. In this way, the sub-components of the coating that cause flash and other effects are preserved, while only color-related toners are adjusted.

[0055] Figure 5 A method 500 for comparing complex coating mixtures with shimmering colors is shown. For example... Figure 5 As shown, action 505 includes receiving an image of the target coating. Action 505 includes receiving at least one image of the target coating. For example, as... Figure 1 As depicted, the coating analysis software application 105 enables the computer system 100 to receive an image 135 of the target coating 130. The image 135 can be, for example, captured by a camera 125 (such as...). Figure 1Image 135 of the target coating 130 may be captured by a spectrophotometer, smartphone, microscope, or any other device capable of scanning the target coating 130 and providing characteristic data related to the properties of the target coating 130. Alternatively or additionally, the image 135 of the target coating 130 includes RGB values ​​from pixel image data. Image 135 may contain associated metadata containing information about camera settings (e.g., magnification, illumination, resolution, camera angle, etc.).

[0056] like Figure 5 As shown, action 510 includes calculating the flash color distribution of an image of the target coating. Action 510 includes calculating the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors.

[0057] For example, Figure 3 illustrates how data from analyzed flash points can be used to calculate a flash color distribution 300, which represents the relative number of flash points of one color to the number of flash points of one or more other colors within the analyzed portion of image 135. The flash color distribution 300 shown in Figure 3 lists the identified colors on the x-axis and the pixel count for each identified color on the y-axis. Although Figure 3 presents the flash color distribution 300 graphically, the coating analysis software application 105 may additionally or alternatively store the data numerically. Those skilled in the art will understand that the colors and pixel counts shown in Figure 3 are merely exemplary.

[0058] Method 500 may further include action 515, which includes searching a database for reference coatings having a flash color distribution that matches the flash color distribution of the target coating. Action 515 includes searching a database for a plurality of reference coatings having a flash color distribution that matches the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution.

[0059] For example, Figure 1 This demonstrates how, once the image processing module 140 calculates the flash color distribution 300, it can search the coating color database 120 for a reference coating with a flash color distribution that matches the flash color distribution 300 of the target coating 130. The coating color database 120 may contain numerical data of the flash color distribution of known coating formulations. The coating color database 120 may also contain additional metadata associated with the flash color distribution data of each known coating formulation. For example, the metadata may contain information about the camera settings (e.g., magnification, illumination, resolution, camera angle, etc.) of the image used to calculate the flash color distribution data of the coating formulation.

[0060] Image processing module 140 can be configured to compare the flash color distribution 300 of image 135 alone with flash color distribution data captured from images having similar associated metadata within coating color database 120. For example, if image 135 is captured at a first angle, then image processing module 140 can search in coating color database 120 for a reference coating having a flash color distribution from an image also captured from the first angle. Alternatively, if a specific camera magnification is used to capture a target coating 130 in image 135, then image processing module 140 can search in coating color database 120 for a reference coating having a flash color distribution from an image including the same camera magnification.

[0061] Figure 5 Further demonstrating action 520 includes calculating the degree to which a reference coating matches a target coating based on the flash color distribution. Action 520 includes calculating the degree to which multiple reference coatings match the target coating based on the flash color distribution. For example, image processing module 140 can use z-score analysis to compare each color within the flash color distribution 300 of image 135 with the corresponding color in the flash color distribution of the reference coating to assign a z-score to each color. The acceptability threshold for each color comparison can be set by the user. The z-score threshold can remain constant or the user can change the threshold according to the quality of the pixel image data. Based on z-score analysis, image processing module 140 can identify the degree to which the target coating 130 matches the analyzed reference coating. The degree of matching can be expressed as a percentage.

[0062] Finally, method 500 may include action 525, which includes generating a list of the closest matching flash color distributions of the reference coatings compared to the flash color distribution of the target coating. Action 525 includes generating a list of the closest matching flash color distributions of the multiple reference coatings compared to the flash color distribution of the target coating.

[0063] For example, Figure 4 A list 400 (e.g., generated by the image processing module 140) displays the closest matching flash color distributions of the reference coatings compared to the flash color distribution 300 of the target coating 130. The graphical user interface 155 can list the reference coatings in order of highest probability. List 400 may include names 410a to 410e and images 420a to 420e for each reference coating, allowing the user to visually compare the depicted colorant images with the target coating 130. Additionally, the graphical user interface 155 may display the calculated correlation percentages 430a to 430e.

[0064] Figure 6 Showing with Figure 5Compared to method 500 shown, an alternative method 600 for comparing complex coating mixtures with shimmering colors is presented. Figure 6 As shown, action 605 includes receiving an image of the target coating. Action 605 includes receiving at least one image of the target coating that includes RGB values ​​from pixel image data. For example, as Figure 1 As depicted, the coating analysis software application 105 enables the computer system 100 to receive an image 135 of the target coating 130. The image 135 can be, for example, captured by a camera 125 (such as...). Figure 1 Image 135 of the target coating 130 may be captured by a spectrophotometer, smartphone, microscope, or any other device capable of scanning the target coating 130 and providing characteristic data related to the properties of the target coating 130. Alternatively or additionally, the image 135 of the target coating 130 includes RGB values ​​from pixel image data. Image 135 may contain associated metadata containing information about camera settings (e.g., magnification, illumination, resolution, camera angle, etc.).

[0065] like Figure 6 As shown, action 610 includes calculating the flash color distribution of an image of the target coating. Action 610 includes calculating the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors.

[0066] For example, Figure 3 illustrates how data from analyzed flash points can be used to calculate a flash color distribution 300, which represents the relative number of flash points of one color to the number of flash points of one or more other colors within the analyzed portion of image 135. The flash color distribution 300 shown in Figure 3 lists the identified colors on the x-axis and the pixel count for each identified color on the y-axis. Although Figure 3 presents the flash color distribution 300 graphically, the coating analysis software application 105 may additionally or alternatively store the data numerically. Those skilled in the art will understand that the colors and pixel counts shown in Figure 3 are merely exemplary.

[0067] Method 600 may further include action 615, which includes searching a database for a reference coating having a flash color distribution that matches the flash color distribution of the target coating. Action 615 includes searching a plurality of reference coatings in the database for a flash color distribution that matches the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution.

[0068] For example, Figure 1This demonstrates how, once the image processing module 140 calculates the flash color distribution 300, it can search the coating color database 120 for a reference coating with a flash color distribution that matches the flash color distribution 300 of the target coating 130. The coating color database 120 may contain numerical data of the flash color distribution of known coating formulations. The coating color database 120 may also contain additional metadata associated with the flash color distribution data of each known coating formulation. For example, the metadata may contain information about the camera settings (e.g., magnification, illumination, resolution, camera angle, etc.) of the image used to calculate the flash color distribution data of the coating formulation.

[0069] Image processing module 140 can be configured to compare the flash color distribution 300 of image 135 alone with flash color distribution data captured from images having similar associated metadata within coating color database 120. For example, if image 135 is captured at a first angle, then image processing module 140 can search in coating color database 120 for a reference coating having a flash color distribution from an image also captured from the first angle. Alternatively, if a specific camera magnification is used to capture a target coating 130 in image 135, then image processing module 140 can search in coating color database 120 for a reference coating having a flash color distribution from an image including the same camera magnification.

[0070] Figure 6 Further demonstrating action 620 includes calculating the degree to which a reference coating matches a target coating using z-score analysis based on flash color distribution. Action 620 includes calculating the degree to which multiple reference coatings match a target coating using z-score analysis based on flash color distribution. For example, image processing module 140 can use z-score analysis to compare each color within flash color distribution 300 of image 135 with the corresponding color in the flash color distribution of the reference coating to assign a z-score for each color. The acceptability threshold for each color comparison can be set by the user. The z-score threshold can remain constant or the user can change the threshold according to the quality of the pixel image data. Based on z-score analysis, image processing module 140 can identify the degree to which the target coating 130 matches the analyzed reference coating. The degree of matching can be expressed as a percentage.

[0071] Finally, method 600 may include action 625, which includes generating a list of the closest matching flash color distributions of the reference coatings compared to the flash color distribution of the target coating. Action 625 includes generating a list of the closest matching flash color distributions of the multiple reference coatings compared to the flash color distribution of the target coating.

[0072] For example, Figure 4A list 400 (e.g., generated by the image processing module 140) displays the closest matching flash color distributions of the reference coatings compared to the flash color distribution 300 of the target coating 130. The graphical user interface 155 can list the reference coatings in order of highest probability. List 400 may include names 410a to 410e and images 420a to 420e for each reference coating, allowing the user to visually compare the depicted colorant images with the target coating 130. Additionally, the graphical user interface 155 may display the calculated correlation percentages 430a to 430e.

[0073] Therefore, in view of this specification, aspects, and claims, one will understand that embodiments of the present invention offer numerous apparent advantages in the art. For example, the systems and methods described herein utilize statistical comparisons of flash color distributions between images to find similar coating colors. At least one system or method described herein can provide accuracy without requiring a spectrophotometer or microscope to fully characterize the target coating. The systems and methods described herein can employ a basic camera capable of basic magnification to capture images of the target coating. Furthermore, because the systems and methods described herein compare the captured image data with known image data, in at least one described system or method, the systems and methods of the present invention can identify similar coating colors using only one image at one angle, thus providing significant advantages.

[0074] Therefore, the computer systems and methods disclosed and claimed herein provide a solution for rapidly identifying special effect pigments and generalizing the ratios of those pigments, thus achieving faster and better color matching while providing higher quality color matching. Furthermore, the coating comparison process disclosed herein can detect subtle color changes that are imperceptible to the human eye.

[0075] Although the subject matter has been described in language specifically addressing structural features and / or methodological actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the described features or actions described above, or the order of the actions described above. In fact, the described features and actions are disclosed as examples of implementing the claims.

[0076] A computer system may include or utilize a special-purpose or general-purpose computer system, which includes computer hardware such as, for example, one or more processors and system memory, as discussed in more detail below. A computer system may also include physical and other computer-readable media for carrying or storing computer-executable instructions and / or data structures. Such computer-readable media may be any available media that can be accessed by a general-purpose or special-purpose computer system. Computer-readable media storing computer-executable instructions and / or data structures are computer storage media. Computer-readable media carrying computer-executable instructions and / or data structures are transmission media. Thus, by way of example and not limitation, a computer system may include at least two distinctly different kinds of computer-readable media: computer storage media and transmission media.

[0077] Computer storage media are physical storage media that store computer-executable instructions and / or data structures. Physical storage media include computer hardware such as RAM, ROM, EEPROM, solid-state drives (“SSDs”), flash memory, phase-change memory (“PCM”), optical disc storage devices, magnetic disk storage devices or other magnetic storage devices, or any other hardware storage device that can be used to store program code in the form of computer-executable instructions or data structures, which can be accessed and executed by general-purpose or special-purpose computer systems to implement the functions disclosed by the computer system.

[0078] The transmission medium may include a network and / or a data link, which may be used to carry program code in the form of computer-executable instructions or data structures and is accessible by a general-purpose or special-purpose computer system. A “network” is defined as one or more data links capable of enabling the transmission of electronic data between computer systems and / or modules and / or other electronic devices. A computer system may consider a network or another communication connection (hardwired, wireless, or a combination of hardwired and wireless) as a transmission medium when information is transmitted or provided to the computer system. The combinations described above should also be included within the scope of computer-readable media.

[0079] Furthermore, upon arrival at various computer system components, program code in the form of computer-executable instructions or data structures can be automatically transferred from the transmission medium to the computer storage medium (or vice versa). For example, computer-executable instructions or data structures received via a network or data link can be cached in the RAM within a network interface module (e.g., a "NIC") and then ultimately transferred to the computer system RAM and / or the low-volatility computer storage medium at the computer system. Therefore, it should be understood that the computer storage medium can be contained within computer system components that also (or even primarily) utilize the transmission medium.

[0080] Computer-executable instructions include, for example, instructions and data that, when executed at one or more processors, cause a general-purpose computer system, a special-purpose computer system, or a special-purpose processing device to perform a function or group of functions. Computer-executable instructions can be, for example, binary, intermediate format instructions (e.g., assembly language), or even source code.

[0081] Those skilled in the art will understand that computer systems can be implemented in network computing environments with various types of computer system configurations, including personal computers, desktop computers, laptop computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, microcomputers, mainframe computers, mobile phones, PDAs, tablet computers, pagers, routers, switches, etc. Computer systems can also be implemented in distributed system environments, where both local and remote computer systems perform tasks via network links (through hardwired data links, wireless data links, or a combination of hardwired and wireless data links). Therefore, in a distributed system environment, a computer system can comprise multiple constituent computer systems. In a distributed system environment, program modules can reside in both local and remote memory storage devices.

[0082] Those skilled in the art will also appreciate that computer systems can be implemented in cloud computing environments. Cloud computing environments can be distributed, but this is not mandatory. When distributed, a cloud computing environment may be distributed internationally within an organization and / or have components owned across multiple organizations. In this specification and the appended claims, “cloud computing” is defined as a model for enabling on-demand networked access to a shared pool of configurable computing resources, such as networks, servers, storage devices, applications, and services. The definition of “cloud computing” is not limited to any of the many other advantages that can be obtained from such a model when properly deployed.

[0083] Cloud computing models can be composed of various characteristics, such as on-demand self-service, broad network access, resource pooling, rapid elasticity, and measurable services. Cloud computing models can also take the form of various service models, such as Software as a Service (“SaaS”), Platform as a Service (“PaaS”), and Infrastructure as a Service (“IaaS”). Furthermore, different deployment models (such as private cloud, community cloud, public cloud, and hybrid cloud) can be used to deploy cloud computing models.

[0084] A cloud computing environment may include a system containing one or more hosts, each capable of running one or more virtual machines. During operation, the virtual machines emulate the operating computing system, thereby supporting an operating system and possibly one or more other applications. Each host may contain a hypervisor that uses physical resources, which are abstracted from the virtual machine's perspective, to simulate virtual resources used by the virtual machine. The hypervisor also provides appropriate isolation between virtual machines. Thus, from the perspective of any given virtual machine, the hypervisor provides the illusion that the virtual machine is interfacing with physical resources, even if the virtual machine is only interfacing with the appearance of physical resources (e.g., virtual resources). Instances of physical resources include processing power, memory, disk space, network bandwidth, media drives, etc.

[0085] In view of the foregoing, the computer system of the present invention relates to, for example but not limited to, the following aspects:

[0086] 1. A computer system for comparing complex coating mixtures with shimmering colors, comprising:

[0087] One or more processors; and

[0088] One or more computer-readable media having executable instructions stored thereon, which, when executed by the one or more processors, configure the computer system to perform at least the following operations:

[0089] Receive at least one image of the target coating;

[0090] Calculate the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors;

[0091] Search a database for a plurality of reference coatings having a flash color distribution that matches the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution;

[0092] The degree to which the plurality of reference coatings match the target coating is calculated based on the flash color distribution; and

[0093] Identify the closest matching reference coating from the plurality of reference coatings.

[0094] 2. The computer system according to aspect 1, wherein the flash color distribution represents the relative number of flash points of each individual color in the measured area compared to the number of flash points of one or more other colors.

[0095] 3. A computer system according to any one of aspects 1 or 2, wherein the executable instructions comprise instructions executable to configure the computer system to perform the following operations:

[0096] Identify the inverted flash color of at least one image of the target coating; and

[0097] The database is searched for multiple reference coatings to further consider matching the reverse flash color of the target coating according to aspects 4 to 6.

[0098] 4. The computer system according to any one of aspects 1 or 3, wherein the executable instructions include instructions executable to configure the computer system to generate a coating adjustment mix to adjust the closest matching reference coating to the target coating.

[0099] 5. The computer system according to any one of aspects 1 to 4, wherein calculating the flash color distribution based on the at least one image of the target coating comprises:

[0100] Analyze at least one image of the target coating to identify at least one flash point; and

[0101] Perform hue analysis to determine the flash color of the at least one flash point.

[0102] 6. The computer system according to any one of aspects 1 to 5, wherein the at least one image of the target coating is captured by a spectrophotometer, camera, smartphone, microscope or other image capturing device.

[0103] 7. A computer system according to any one of aspects 1 to 6, wherein the executable instructions include instructions executable to configure the computer system to generate a list of the nearest matching flash color distributions of the plurality of reference coatings compared to the flash color distribution of the target coating.

[0104] 8. The computer system according to aspect 4 or with reference to aspects 5 to 7 of aspect 4, wherein generating the coating adjustment formulation includes generating a list of toners.

[0105] 9. A computerized method for use on a computer system comprising one or more processors and one or more computer-readable media, said one or more computer-readable media having executable instructions stored thereon, said executable instructions, when executed by said one or more processors, configuring said computer system to perform, for example, a method for comparing complex coating mixtures having shimmering colors on a computer system as defined in aspects 1 to 8, said method comprising:

[0106] Receive at least one image of the target coating;

[0107] Calculate the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors;

[0108] Search a database for a plurality of reference coatings having a flash color distribution that matches the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution;

[0109] The degree to which the plurality of reference coatings match the target coating is calculated based on the flash color distribution; and

[0110] Generate a list of the closest matching flash color distributions of the plurality of reference coatings compared to the flash color distribution of the target coating.

[0111] 10. The method according to aspect 9, wherein:

[0112] At least one image of the target coating is captured at a first angle; and

[0113] The database contains the flash color distribution of images of the reference coating captured at more than one angle.

[0114] 11. The method according to any one of aspects 9 or 10, wherein searching the database further comprises searching the database for the plurality of reference coatings having a flash color distribution from an image captured at the first angle, the flash color distribution matching the flash color distribution of the target coating captured at the first angle.

[0115] 12. The method according to any one of aspects 9 to 11, further comprising:

[0116] Receive at least one additional image of the target coating captured at at least one additional angle;

[0117] The flash color distribution is calculated based on the at least one additional image of the target coating captured at the at least one additional angle; and

[0118] The database is searched for additional reference coatings having flash color distributions from images captured at the at least one additional angle, the flash color distributions being matched with the flash color distributions of the additional images of the target coating captured at the at least one additional angle.

[0119] 13. The method according to any one of aspects 9 to 12, wherein the at least one image of the target coating is captured by a camera.

[0120] 14. The method according to any one of aspects 9 to 13, wherein the at least one image of the target coating comprises RGB values ​​from pixel image data.

[0121] 15. The method according to any one of aspects 9 to 14, further comprising using the closest matching flash color distribution to select the closest matching reference coating.

[0122] 16. The method according to aspect 15, further comprising generating a coating adjustment formulation to adjust the closest matching reference coating to the target coating.

[0123] 17. The computerized method according to any one of aspects 9 to 16, further comprising:

[0124] Analyze at least one image of the target coating to identify at least one flash point; and

[0125] Perform hue analysis to determine the flash color of the at least one flash point.

[0126] 18. A computerized method for use on a computer system, or a method according to any one of aspects 9 to 17, comprising one or more processors and one or more computer-readable media storing executable instructions thereon, the executable instructions, when executed by the one or more processors, configuring the computer system to perform, for example, a method for comparing complex coating mixtures having shimmering colors on a computer system as defined in aspects 1 to 8, the method comprising:

[0127] Receive at least one image of a target coating that includes RGB values ​​from pixel image data;

[0128] Calculate the flash color distribution of at least one image of the target coating, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors;

[0129] Search the database for multiple reference coatings with flash color distributions that match the target coating;

[0130] The degree to which the multiple reference coatings match the target coating is calculated using z-score analysis based on the flash color distribution; and

[0131] Generate a list of the closest matching flash color distributions of the plurality of reference coatings compared to the flash color distribution of the target coating.

[0132] 19. The method according to aspect 18, wherein the quality of the pixel image data affects a threshold set in the z-score analysis.

[0133] 20. The method according to any one of aspects 18 or 19, further comprising using the closest matching flash color distribution to select the closest matching reference coating.

[0134] 21. The method according to any one of aspects 18 to 20, wherein the z-score analysis uses the following z-score formula:

[0135]

[0136] Where z is the z-score. The proportion of individual color pixels in the first coating to the total number of pixels of all colors. The proportion of individual color pixels in the second coating relative to the total number of pixels of all colors. Let n1 be the proportion of individual color pixels in the two coatings to the total number of pixels in the two coatings, and n2 be the total number of pixels in the first coating and n2 be the total number of pixels in the second coating.

[0137] Although the subject matter has been described in language specifically addressing structural features and / or methodological actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the described features or actions described above, or the order of the actions described above. In fact, the described features and actions are disclosed as examples of implementing the claims.

Claims

1. A computer system for comparing complex coating mixtures with shimmering colors, comprising: One or more processors; as well as One or more computer-readable media having executable instructions stored thereon, which, when executed by the one or more processors, configure the computer system to perform at least the following operations: Receive at least one image of the target coating; The flash color distribution of at least one image of the target coating is calculated by isolating high-intensity pixels in the image to identify flash points, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors. Search a database for a plurality of reference coatings having a flash color distribution that matches the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution; The degree to which the plurality of reference coatings match the target coating is calculated based on the flash color distribution; as well as Identify the closest matching reference coating from the plurality of reference coatings.

2. The computer system of claim 1, wherein the flash color distribution represents the relative number of flash points of each color in the measured area compared to the number of flash points of one or more other colors.

3. The computer system of claim 1 or 2, wherein the executable instructions comprise instructions executable to configure the computer system to perform the following operations: Identify the inverted flash color of at least one image of the target coating; and The database is searched for multiple reference coatings, and the reverse flash color of multiple reference coatings that match the reverse flash color of the target coating is further considered.

4. The computer system of claim 1 or 2, wherein the executable instructions include instructions executable to configure the computer system to generate a coating adjustment mix to adjust the closest matching reference coating to the target coating.

5. The computer system according to claim 1 or 2, wherein calculating the flash color distribution based on the at least one image of the target coating comprises: Analyze at least one image of the target coating to identify at least one flash point; as well as Perform hue analysis to determine the flash color of the at least one flash point.

6. The computer system according to claim 1 or 2, wherein the at least one image of the target coating is captured by a spectrophotometer, camera, smartphone, microscope or other image capturing device.

7. The computer system of claim 1 or 2, wherein the executable instructions comprise instructions executable to configure the computer system to generate a list of the nearest matching flash color distributions of the plurality of reference coatings compared to the flash color distribution of the target coating.

8. The computer system of claim 4, wherein generating the coating adjustment formulation includes generating a list of toners.

9. A computerized method for use on a computer system comprising one or more processors and one or more computer-readable media, the one or more computer-readable media having executable instructions stored thereon, the executable instructions, when executed by the one or more processors, configuring the computer system to compare complex coating mixtures having a shimmering color, the method comprising: Receive at least one image of the target coating; The flash color distribution of at least one image of the target coating is calculated by isolating high-intensity pixels in the image to identify flash points, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors. Search a database for a plurality of reference coatings having a flash color distribution that matches the flash color distribution of the target coating, wherein each of the plurality of reference coatings has a different flash color distribution; The degree to which the plurality of reference coatings match the target coating is calculated based on the flash color distribution; as well as Generate a list of the closest matching flash color distributions of the plurality of reference coatings compared to the flash color distribution of the target coating.

10. The method according to claim 9, wherein: At least one image of the target coating is captured at a first angle; and The database contains the flash color distribution of images of the reference coating captured at more than one angle.

11. The method of claim 9 or 10, wherein searching the database further comprises searching the database for the plurality of reference coatings having a flash color distribution from an image captured at the first angle, the flash color distribution matching the flash color distribution of the target coating captured at the first angle.

12. The method of claim 11, further comprising: Receive at least one additional image of the target coating captured at at least one additional angle; The flash color distribution is calculated based on the at least one additional image of the target coating captured at the at least one additional angle; as well as The database is searched for additional reference coatings having flash color distributions from images captured at the at least one additional angle, the flash color distributions being matched with the flash color distributions of the additional images of the target coating captured at the at least one additional angle.

13. The method of claim 9 or 10, wherein the at least one image of the target coating is captured by a camera.

14. The method of claim 9 or 10, wherein the at least one image of the target coating comprises RGB values ​​from pixel image data.

15. The method of claim 9 or 10, further comprising using the closest matching flash color distribution to select the closest matching reference coating.

16. The method of claim 15, further comprising generating a coating adjustment formulation to adjust the closest matching reference coating to the target coating.

17. The computerized method according to claim 9 or 10, further comprising: Analyze at least one image of the target coating to identify at least one flash point; as well as Perform hue analysis to determine the flash color of the at least one flash point.

18. A computerized method for use on a computer system comprising one or more processors and one or more computer-readable media, the one or more computer-readable media having executable instructions stored thereon, the executable instructions, when executed by the one or more processors, configuring the computer system to compare a complex coating mixture having a shimmering color, the method comprising: Receive at least one image of a target coating that includes RGB values ​​from pixel image data; The flash color distribution of at least one image of the target coating is calculated by isolating high-intensity pixels in the image to identify flash points, wherein the flash color distribution represents the relative number of flash points of one color in the measured area compared to the number of flash points of one or more other colors. Search the database for multiple reference coatings with flash color distributions that match the target coating; The degree to which the multiple reference coatings match the target coating is calculated using z-score analysis based on the flash color distribution; as well as Generate a list of the closest matching flash color distributions of the plurality of reference coatings compared to the flash color distribution of the target coating.

19. The method of claim 18, wherein the quality of the pixel image data affects a threshold set in the z-score analysis.

20. The method of claim 18 or 19, further comprising using the closest matching flash color distribution to select the closest matching reference coating.

21. The method of claim 18 or 19, further comprising generating a coating adjustment formulation to adjust the closest matching reference coating to the target coating.

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