A system for detection and coating analysis that comprises a digital camera and a light-based protractor positioned adjacent to or on a physical coating surface. The system identifyies a particular angular indication being displayed by the light-based protractor. The system then identifies a target color of the physical coating surface and identifies one or more target coating texture characteristics of the physical coating surface. Additionally, the system identifies a proposed coating that comprises a proposed color that matches the target color and proposed coating characteristics that match the one or more target coating texture characteristics. The system then displays, on a user interface, the proposed coating.

Embodiments of the invention generally relate to color and appearance metric measurements and, in particular, developing instrumentation to enable self-consistent image appearance measurements within instruments of unitary construction.

A system for detection and coating analysis that comprises a digital camera and a light-based protractor positioned adjacent to or on a physical coating surface. The system identifies a particular angular indication being displayed by the light-based protractor. The system then identifies a target color of the physical coating surface and identifies one or more target coating texture characteristics of the physical coating surface. Additionally, the system identifies a proposed coating that comprises a proposed color that matches the target color and proposed coating characteristics that match the one or more target coating texture characteristics. The system then displays, on a user interface, the proposed coating.

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.

A device such as a stylus may have a color sensor. The color sensor may have a color sensing light detector having a plurality of photodetectors each of which measures light for a different respective color channel. The color sensor may also have a light emitter. The light emitter may have an adjustable light spectrum. The light spectrum may be adjusted during color sensing measurements using information such as ambient light color measurements made with a color ambient light sensor that has a plurality of photodetectors each of which measures light for a different respective color channel. An inertial measurement unit may be used to measure the angular orientation between the stylus and an external object during color measurements. Arrangements in which the light emitter is modulated during color sensing may also be used. Measurements from the stylus may be transmitted wirelessly to external equipment.

Disclosed in a method, a user interface and a system for use in determining shade of a patient's tooth, wherein a digital 3D representation including shape data and texture data for the tooth is obtained. A tooth shade value for at least one point on the tooth is determined based on the texture data of the corresponding point of the digital 3D representation and on known texture values of one or more reference tooth shade values.

Described herein is a computer-implemented method and a system for providing a match metric for quantifying a spectral similarity of a target coating and at least one sample coating, the system including a computing device that performs a computing process, the computing process including: receiving reflectance values of the target coating and the sample coating; normalizing each of the reflectance values; generating a normalized reflectance curve for the target coating and for the sample coating; producing derivative values of the normalized reflectance curve of the target coating and derivative values of the normalized reflectance curve of the sample coating with respect to the wavelength; producing difference values between the derivative values of the target coating and the derivative values of the sample coating; and producing a match metric for a similarity between the normalized reflectance curves of the target coating and the sample coating.

Described herein is a computer-implemented method for providing a match metric for matching and adjusting color of a target coating and at least one sample coating, the method including at least the steps of: obtaining, via at least one communications interface, spectral curve(s) of the target coating and spectral curves of the sample coating determined at at least one gloss geometry; producing normalized first derivative values of the normalized spectral curves of the target coating and of the sample coating; producing difference values between the normalized first derivative values of the target coating and of the sample coating; producing a first match metric for the target coating and the sample coating based at least on the difference values produced for the at least one gloss geometry; and producing the match metric based on the first match metric. Also described herein is a respective system.

A surface characteristics evaluation method for evaluating a surface characteristic of a painted surface including a glittering material, including: a multi-angle condition image acquisition step S101 for acquiring a multi-angle condition image including multi-angle conditions in a continuous manner by performing an image-capturing process to capture how a reflection condition of the painted surface changes when rotating an illumination device 2 emitting light onto the painted surface, the image-capturing process being performed by the line scan camera 4 while a sample P having the painted surface is moved in a certain direction; an in-plane chromaticity distribution acquisition step S102 for acquiring an in-plane chromaticity distribution of the painted surface from the multi-angle condition image acquired; and a surface characteristics evaluation step S107 for calculating particle characteristics S as surface characteristics evaluation values of the multi-angle conditions, on the basis of the in-plane chromaticity distribution acquired.

An aluminum can that has a maximum height of roughness Rz1 in the circumferential direction of not more than 0.5 μm on the outer surface of the thinnest portion of the body portion and, as viewed on the side surface, has a ratio Ra1/Ra2 in a range of 0.8 to 1.2, the ratio Ra1/Ra2 being that of a mean surface roughness Ra1 in the circumferential direction on the outer surface of the thinnest portion of the body portion and a mean surface roughness Ra2 in the circumferential direction on the outer surface of the lower end portion of the body portion.