JP-7855074-B2 - Color adjustment method and system

JP7855074B2JP 7855074 B2JP7855074 B2JP 7855074B2JP-7855074-B2

Inventors

ビショフ，グイド
ヴィニョーロ，カルロス

Assignees

ビーエーエスエフコーティングスゲゼルシャフトミットベシュレンクテルハフツング

Dates

Publication Date: 20260507
Application Date: 20230109
Priority Date: 20220111

Claims (15)

A computer-implemented method for determining the formulation of a sample coating adjusted to match the color of a reference coating, wherein the method is: (i) A digital representation of the sample coating, including the sample coating's color data and its formulation, is transmitted to a computer processor via a communication interface. - Digital representation of the reference coating, including the color data of the reference coating, - Digital representation of individual color components, including optical data for each color component, A physical model configured to predict the color of a sample coating by using the formulation of the sample coating and the optical data of individual color components as input parameters, The steps to provide, (ii) A step in which a computer processor determines the color difference between the provided sample coating color data and the provided reference coating color data, (iii) The model bias of the provided physical model is processed by a computer processor. - Predicting the color data of the sample coating based on the digital representation of the sample coating, the digital representation of the individual color components, and the physical model provided in step (i), - To determine the color difference between the provided sample coating color data and the predicted sample coating color data, The steps to be determined by, (iv) A step in which the model bias determined in step (iii) is minimized by a computer processor by fitting the provided optical data of at least some of the individual color components present in the sample coating formulation, (v) A step in which the residual model bias is determined by a computer processor by determining the color difference between the provided color data and the predicted color data of the sample coating using the optical data fitted in step (iv), (vi) A step in which a computer processor calculates the adjusted sample coating formulation based on the color difference determined in step (ii), the fitted optical data of the individual color components obtained in step (iv), the residual model bias determined in step (v), and the provided physical model, (vii) The step of providing the calculated adjusted sample coating formulation via a communication interface, Methods that include...
The method according to claim 1, wherein the digital representation of the sample coating further includes data indicating the sample coating, the layer structure of the sample coating, instructions for preparing the sample coating formulation, price, or a combination thereof.
The method according to claim 1 or 2, wherein the digital representation of the reference coating further includes data indicating the reference coating, the layer structure of the reference coating, the formulation related to the reference coating, instructions for preparing the reference coating formulation, price, or a combination thereof.
The method according to claim 1 or 2, wherein the color data includes reflectance data, color space data , or a combination thereof.
The method according to claim 1 or 2, wherein the optical data for each color component includes the optical constants of each color component.
The method according to claim 1 or 2, wherein the color of the sample coating is predicted in step (iii) using the optical data of the sample coating formulation and the individual color components present within the sample coating formulation as input parameters of a provided physical model.
Minimizing the model bias determined in step (iii) is: - A numerical method is provided which is configured to match the optical data of at least some of the individual color components present in a sample coating formulation by starting from the optical data provided in step (i) and minimizing a predetermined cost function, The method according to claim 1 or 2, further comprising the step of fitting optical data of at least some of the individual color components present in the sample coating formulation using the provided numerical method and the provided physical model, by comparing the provided color data of the sample coating obtained using the provided physical model with the color data of the provided sample coating until the cost function falls below a predetermined threshold or the number of iterations reaches a predetermined limit.
The method according to claim 7, wherein fitting the optical data of at least some of the individual color components present in the sample coating formulation includes applying a scaling function to the optical data.
The scaling function includes the linear scaling function of equation (1), Here Refers to the adapted optical data , It refers to an index, ranging from 1 to n. The method according to claim 8, wherein the range is from 1 to m.
The method according to claim 9, which is used for optical data that is wavelength-dependent for all individual color components.
Calculating the corrected sample coating formulation - A numerical method is provided which is configured to adjust the concentration of at least one individual color component present in a sample coating formulation by starting from the concentrations of individual color components contained in a digital representation of a provided sample coating and minimizing a predetermined cost function. - A step of adjusting the concentration of at least one individual color component present in the sample coating formulation by comparing the recursively predicted color data of the recursively adjusted formulation of the sample coating with the color data of a provided reference coating, using the provided numerical method, the adapted optical data obtained in step (iv), the residual model bias, and the provided physical model, until the color difference falls below a predetermined threshold or the number of iterations reaches a predetermined limit. The method according to claim 1 or 2, including the method described in claim 1 or 2.
A computing device for determining the formulation of a sample coating adjusted to match the color of a reference coating, wherein the computing device : - A communication interface, 〇 Digital representation of the sample coating, including the color data and formulation of the sample coating, ○ Digital representation of the reference coating, including the color data of the reference coating, ○ Digital representation of individual color components, including optical data for each color component, A physical model configured to predict the color of a sample coating by using the formulation of the sample coating and the optical data of individual color components as input parameters, A communication interface to provide, - A processing module that communicates with the aforementioned communication interface, wherein the processing module comprises at least one computer processor, - A memory that stores instructions configured to cause a computing device to perform the steps of the computer implementation method described in claim 1 when executed by the processing module, A computing device equipped with the following features.
A non-transient computer-readable storage medium, wherein the computer-readable storage medium includes an instruction that, when executed by the computing device of claim 12, causes the computing device to perform a step according to the method of claim 1 or 2.
The use of the method according to claim 1 or the computing device according to claim 12 in a color adjustment process.
A system comprising a server device and a client device, wherein the client device is for determining a sample coating formulation adjusted to match the color of a reference coating in the server device, the client device is configured to provide the server device with a digital representation of the sample coating including color data of the sample coating and the sample coating formulation, a digital representation of the reference coating including color data of the reference coating, and a digital representation of individual color components including optical data of the individual color components, the server device being the computing device of claim 12.

Description

The embodiments described herein generally relate to methods and systems for adjusting the color of a sample coating to the color of a reference coating so that a good color match can be obtained. More specifically, the embodiments described herein relate to methods and systems for determining a modified sample coating formulation that closely matches the color of a reference coating by determining fitted optical data for the individual color components present in the sample coating formulation when applied to a substrate, and using the fitted optical data to determine the modified sample coating formulation. By using fitted optical data for the individual color components present in the sample coating formulation in the color adjustment process, variations in the colorant strength characteristics of colorants in paint manufacturing can be compensated for. The fitting of the optical data can improve the quality and/or accuracy of the adjusted sample coating formulation, and therefore the number of adjustment steps required to obtain the desired color of the sample coating relative to the reference coating can be reduced. The paint manufacturing process for a given color standard typically begins with an initial coating formulation, such as a formula read from a database. The color of the initial coating formulation is obtained by adding at least one pigment paste (hereinafter also referred to as a colorant) to a base varnish containing a binder, solvent, and optionally additives. The pigment paste is an intermediate product containing coloring components (such as pigments) in a matrix (typically a binder, solvent, and optionally additives). Typically, the color of the intermediate product varies from batch to batch due to variations in the quality of raw materials such as pigments. To avoid adjusting the color of each pigment paste produced, the pigment paste is used "as is" for the preparation of the initial coating formulation, so that only the initial coating formulation needs to be adjusted. Typically, the initial coating formulation contains a reduced amount of pigment paste (compared to the final paint formulation) to avoid the manufactured coating batch becoming too dark due to an overshoot in the color intensity characteristics of one or more colorants present in the coating formulation. The initial coating batch is manufactured according to this initial coating formulation, and the corresponding color of this coating batch is measured and compared to the reference color. Due to the reduced amount of colorant, the initial coating batch typically exhibits a significant residual color difference compared to the reference coating. Therefore, to minimize the residual color difference between the coating batch and the reference coating, a color adjustment process must be applied by modifying the initial coating formulation. Next, the modified coating is prepared from the modified initial coating formulation, its color is determined, and it is compared to the reference coating color. If the match is insufficient, the color adjustment process must be repeated with the modified initial coating formulation. Most computer-aided color matching methods are based on physical models that describe the interaction between light and a scattering or absorbing medium, such as a colorant in a coating layer. Each coating layer has specific light reflectivity characteristics due to the colorants present in that layer. Each of these colorants has specific optical properties represented by its respective optical constants or optical data. These optical constants describe the absorption and scattering characteristics of these colorants in the environment of the physical model, such as the K/S values in the well-known Kubelka/Munk model. Physical models like the Kubelka/Munk model can predict the light reflectivity characteristics (color) of a coating layer based on information about the colorants present in the coating layer (e.g., information about the formulation used to prepare the coating layer), along with the corresponding optical properties or respective optical constants of the colorants. The optical properties of a colorant can be determined based on the color data of an existing reference coating prepared from a known coating formulation with known reflectance data. Therefore, the color prediction and matching process of the physical model always uses the optical properties of the colorant present in the batch used to prepare the reference coating (hereinafter also referred to as the "reference colorant batch"). A suitable formulation (or appropriate color adjustment) for a given reference color can be predicted using a numerical optimization algorithm based on a physical model that has existing optical constants of the colorant and reflectance data of the reference coating as input parameters. However, the accuracy of the color prediction by the physical model is limited by the presence of systematic and statisti