Abstract: A system and method include receiving target image data associated with a target coating. A feature extraction analysis process is applied to the target image data to determine a target image feature. The feature extraction analysis process includes dividing the target image into sub-images which contains a plurality of target pixels. A machine learning model identifies one or more types of flakes present in the target coating using target pixel features.

Abstract: Systems and methods for a sample database are provided, where the sample database is for matching a target coating. In one embodiment, the system comprises a sample database stored on a storage device. The sample database includes a sample coating formula and a sample image feature with at least one sample coating formula linked to at least one sample image feature. At least one sample image feature includes a spatial micro-color analysis that includes a value determined by a sample pixel feature difference between at least two sample pixels.

Abstract: A computing system and associated methodology of evaluating and matching colored sparkle appearance of coatings containing at least one effect pigment type are disclosed. The methodology processes a digital image of a coating sample obtain pixel-specific sparkle point data and pixel-specific background data, both of which are formatted in accordance with an advanced color appearance model that corresponds to human color perception. A colored sparkle visual scaling value is calculated from the pixel-specific data, wherein the visual scaling value indicates colored sparkle characteristics of the coating sample. The visual scaling value of the coating sample is compared against the visual scaling value of a previously-characterized candidate coating specimen. The results of the comparison are used to determine how well the candidate coating specimen matches (in colored sparkle characteristics) the coating sample.

Abstract: Systems and methods for a sample database are provided, where the sample database is for matching a target coating. In one embodiment, the system comprises a sample database stored on a storage device. The sample database includes a sample coating formula and a sample image feature with at least one sample coating formula linked to at least one sample image feature. At least one sample image feature includes a spatial micro-color analysis that includes a value determined by a sample pixel feature difference between at least two sample pixels.

Abstract: Systems and methods for determining a matting agent level for a clearcoat formulation for repairing an object are disclosed. The method comprises the following steps: a) providing a database with multiple datasets, each dataset including a first gloss level value of a sample coating determined at a first measurement geometry and a matting agent level; b) determining a second gloss level value of the sample coating with a measurement arrangement at a second measurement geometry; c) associating the second gloss level value to the dataset of the sample coating; d) determining a third gloss level value of a target coating with the measurement arrangement at the second measurement geometry; e) selecting, from the database, a target dataset with a second gloss level value that is closest to the third gloss level value; and f) determining, from the target dataset, the matting agent level for the clearcoat formulation.

Abstract: A system and method include receiving target image data associated with a target coating. A texture feature extraction analysis process is applied to the target image data to determine a target texture image feature. A machine learning model identifies one or more texture features for matching to a target coating.

Abstract: A system and method include receiving target image data associated with a target coating. A texture feature extraction analysis process is applied to the target image data to determine a target texture image feature. A machine learning model identifies one or more texture features for matching to a target coating.

Abstract: A computing system and associated methodology of evaluating and matching colored sparkle appearance of coatings containing at least one effect pigment type are disclosed. The methodology processes a digital image of a coating sample obtain pixel-specific sparkle point data and pixel-specific background data, both of which are formatted in accordance with an advanced color appearance model that corresponds to human color perception. A colored sparkle visual scaling value is calculated from the pixel-specific data, wherein the visual scaling value indicates colored sparkle characteristics of the coating sample. The visual scaling value of the coating sample is compared against the visual scaling value of a previously-characterized candidate coating specimen. The results of the comparison are used to determine how well the candidate coating specimen matches (in colored sparkle characteristics) the coating sample.

Abstract: A system and method include receiving target image data associated with a target coating. A feature extraction analysis process is applied to the target image data to determine a target image feature. The feature extraction analysis process includes dividing the target image into sub-images which contains a plurality of target pixels. A machine learning model identifies one or more types of flakes present in the target coating using target pixel features.

Abstract: A system and method include receiving target image data associated with a target coating. A feature extraction analysis process is applied to the target image data to determine a target image feature. The feature extraction analysis process includes dividing the target image into sub-images which contains a plurality of target pixels. A machine learning model identifies one or more types of flakes present in the target coating using target pixel features.

Abstract: Devices and methods for measuring color of a target coating are provided. In an exemplary embodiment, a color measurement device includes a housing configured for placement on a target coating. A source connected to the housing directs a beam of electromagnetic radiation towards the target coating at an entrance angle. A spherical coordinate system is used, where the entrance angle is a polar angle measured from a zenith that is normal to the target coating surface. First and second detectors are connected to the housing at a first and second polar angle, respectively, to measure the electromagnetic radiation reflected by a target population of flakes within the target coating, where all the flakes in the target population of flakes have the same angled flake normal polar angle. The first polar angle is different than the second polar angle.

Abstract: Processor implemented systems and methods for matching color and appearance of a target coating are provided herein. A system includes a storage device for storing instructions, and one or more data processors. The data processor(s) are configured to execute instructions to receive a target image of a target coating. The data processor(s) are also configured to apply a feature extraction analysis process that divides the target image into a plurality of target pixels for image analysis.

Abstract: Apparatuses and methods for approximating a 5-angle color difference model are provided, where the 5-angle color difference model utilizes a 5-angle equation. In an exemplary embodiment, an apparatus includes a storage device for storing instructions and one or more processors configured to execute the instructions. The processor(s) are configured to receive 3-angle standard and test color measurements, and enter the 3-angle standard measurement into a neural network empirical model. The neural network empirical model includes a plurality of input nodes, a plurality of hidden nodes connected to the input nodes, and a plurality of output nodes connected to the hidden nodes. The neural network empirical model is configured to output 3-angle tolerance values, and to calculate a 3-angle color difference value using the 5-angle equation for at least one of the 3 color measurement angles using the 3-angle standard and test color measurements and the 3-angle tolerance values.

Abstract: A system and method include receiving target image data associated with a target coating. A color model and a local color model are used to predict color differences between the target coating and a sample coating. The color model and local color model includes a feature extraction analysis process that determines image features by analyzing target pixel feature differences within the target coating. Performing an optimization routine upon the color differences for determining automotive paint components for spraying a substrate.

Abstract: System and methods for matching color and appearance of a target coating are provided herein. The system includes an electronic imaging device configured to receive a target image data of the target coating. The target image data includes target coating features. The system further includes one or more feature extraction algorithms that extracts the target image features from the target image data. The system further includes a machine-learning model that identifies a calculated match sample image from a plurality of sample images utilizing the target image features. The machine-learning model includes pre-specified matching criteria representing the plurality of sample images for identifying the calculated match sample image from the plurality of sample images. The calculated match sample image is utilized for matching color and appearance of the target coating.

Abstract: Systems and methods for determining illumination angle and viewing angle in color observation are described. The system includes an optical capturing device to acquire an image of its surroundings and a processing unit. When operated, the processing unit executes the following steps: identify a position of a light source in the image acquired by the optical capturing device; identify a position of a viewer in the image acquired by the optical capturing device; determine a first angular position of the light source with respect to the optical capturing device and a second angular position of the viewer with respect to the optical capturing device and provide the first angular position and the second angular position to define an actual viewing geometry.

Abstract: Devices and methods for measuring color of a target coating are provided. In an exemplary embodiment, a color measurement device includes a housing configured for placement on a target coating. A source connected to the housing directs a beam of electromagnetic radiation towards the target coating at an entrance angle. A spherical coordinate system is used, where the entrance angle is a polar angle measured from a zenith that is normal to the target coating surface. First and second detectors are connected to the housing at a first and second polar angle, respectively, to measure the electromagnetic radiation reflected by a target population of flakes within the target coating, where all the flakes in the target population of flakes have the same angled flake normal polar angle. The first polar angle is different than the second polar angle.

Abstract: System and methods for matching color and appearance of a target coating are provided herein. The system includes an electronic imaging device configured to receive a target image data of the target coating. The target image data includes target coating features. The system further includes one or more feature extraction algorithms that extracts the target image features from the target image data. The system further includes a machine-learning model that identifies a calculated match sample image from a plurality of sample images utilizing the target image features. The machine-learning model includes pre-specified matching criteria representing the plurality of sample images for identifying the calculated match sample image from the plurality of sample images. The calculated match sample image is utilized for matching color and appearance of the target coating.

Abstract: Processor implemented systems and methods for matching color and appearance of a target coating are provided herein. A system includes a storage device for storing instructions, and one or more data processors. The data processor(s) are configured to execute instructions to receive a target image of a target coating. The data processor(s) are also configured to apply a feature extraction analysis process that divides the target image into a plurality of target pixels for image analysis.

Abstract: A system for displaying one or more images to select one or more matching formulas to match color and appearance of a target coating of an article includes a computing device, a display device, a host computer connected to the computing device, one or more data input devices, a first database containing repair formulas, color characteristics, and appearance characteristics, a second database containing identification information of an article or a three-dimensional model of an article or a three-dimensional mapping of a geometry of a part of an article, and a computer program product accessible to the computing device and/or the host computer and performing a computing process to retrieve at least one preliminary matching formula from the first database, select one article or a three-dimensional mapping of a geometry of one article from the second database, generate individual matching images, and display the individual matching images on the display device.