Abstract:
Systems and methods for color calibrating an image are described herein. In some embodiments, a method includes disposing a unique identifier and a fiducial marker that includes a plurality of color regions on an object. A first image of the object is captured with a first camera and a second image of the object that is captured with a second camera is received. The second image is associated with the first image based on the unique identifier and spectral information of at least a portion of the fiducial marker in the second image is compared with spectral information of at least the portion of the fiducial marker in the first image. Based on the comparison, the second image is resampled to substantially match at least the portion of the fiducial marker in the second image to at least the portion of the fiducial marker in the first image.
Abstract:
A computer-implemented method for identifying an effect pigment, the method comprising executing, on at least one processor of at least one computer, steps of: a) acquiring sample image data describing a digital image of a layer comprising a sample effect pigment b) determining, based on the sample image data, sparkle point data describing a sample distribution of sparkle points defined by the digital image, wherein the sample distribution is defined in an N-dimensional color space, wherein N is an integer value equal to or larger than 3; c) determining, based on the sparkle point data, sparkle point transformation data describing a transformation of the sample distribution into an (N-1)-dimensional color space; d) determining, based on the sparkle point transformation data, sparkle point distribution geometry data describing a geometry of the sample distribution; e) acquiring reference distribution geometry data describing a geometry of a reference distribution of sparkle points in the (N-1)-dimensional color space; f) acquiring reference distribution association data describing an association between the reference distribution and an identifier of the reference distribution; g) determining, based on the sparkle point distribution geometry data and the reference distribution geometry data and the reference distribution association data, sample pigment identity data describing an identity of the sample effect pigment.
Abstract:
A computerized method for displaying matches of a paint sample to various proposed paint coatings includes receiving one or more coating texture variables of a target coating from a coating-measurement instrument. The method also includes displaying, on a digital display device, effect texture ratings for multiple respective proposed coating matches on a digital display device, wherein the effect texture ratings indicate a similarity between the one or more coating texture variables of the target coating and respective coating textures variables of each of the respective proposed coating matches. In addition, the method includes ordering the proposed coating matches, wherein the ordering indicates a strength in similarity between the target coating and each of the proposed coating matches with respect to the effect texture ratings.
Abstract:
A method for calculating a coating textures indicator can comprise receiving target coating texture variables from an image. The method can also comprise accessing a relative texture characteristic database that stores a set of texture characteristic relationships for a plurality of coatings. The method can further comprise calculating a correlation between the target coating texture variables and target coating texture variables associated with a compared coating. Based upon the calculated correlation, the method can comprise, calculating a set of relative texture characteristics for the target coating that indicate relative differences in texture between the target coating and the compared coating. Each of the relative texture characteristics can comprise an assessment over all angles of the target coating.
Abstract:
A bet sensor for sensing values of gaming tokens may include a bet placement surface configured and oriented to support a stack of gaming tokens thereon and an image sensor located and oriented to capture an image of a lateral side surface of at least one gaming token located on the bet placement surface. The image may depict the lateral side surface in a radial format. The bet sensor may include a processor in communication with the image sensor. The processor is configured to acquire image data from the image and analyze the image data to determine a wager value of the at least one token. A gaming table may include such a bet sensor. The disclosure includes methods of operating such a gaming table.
Abstract:
The disclosure relates to a method for calibrating colors of at least one display device, called a target device, from another display device, called a reference device, said target device being associated with a first rendering function, and said reference device being associated with a second rendering function, said first and second rendering functions being associated with respectively a first set of parameters and a second set of parameters. The method comprises: displaying on the target device at least two pixels with encoded colors (Ci), viewed by a user on the target device as first perceived colors (P T i), said encoded colors (Ci) being viewed by the user on the reference device as second perceived colors (P R i); modifying the encoded colors (Ci) on the target device, delivering modified encoded colors (Ci') viewed by the user on the target device as modified perceived colors (P T i'), corresponding to the second perceived colors (P R i), via a user's input; determining a first and a second set of modified parameters for respectively said first and second rendering functions, so that encoded colors may be perceived similarly on the target and reference devices; correcting an encoded color of at least another pixel to be displayed on the target device, using said first and second set of modified parameters.
Abstract:
The invention relates to a method to determine a formula for a sample color matching a target color, based on an obsolete color formula, based on a given range of tinting bases. According to the proposed method, a color prediction model is used to calculate a distance between respective color parameters of a candidate color formula and the color parameters of the target color, and a genetic algorithm is used to obtain the formula for the sample color out of a population of candidate color formulas, wherein a distance of respective color parameters of a candidate color formula of the population of candidate color formulas to the color parameters of the target color is minimized by the genetic algorithm by iterative steps of mutation/crossing-over and selection of candidate color formulas that fit best to a fitness criterion, until a pre-given stopping criterion is fulfilled which automatically leads to a candidate color formula which is kept as the sample color formula.