CN113976037A - Computer-aided same-color same-spectrum paint color matching method - Google Patents
Computer-aided same-color same-spectrum paint color matching method Download PDFInfo
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- 238000001228 spectrum Methods 0.000 title claims abstract description 74
- 238000000034 method Methods 0.000 title claims abstract description 64
- 239000003973 paint Substances 0.000 title claims abstract description 33
- 239000000049 pigment Substances 0.000 claims abstract description 162
- 230000003595 spectral effect Effects 0.000 claims abstract description 50
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- 230000003287 optical effect Effects 0.000 claims abstract description 21
- 238000004364 calculation method Methods 0.000 claims abstract description 20
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- 238000005094 computer simulation Methods 0.000 claims abstract description 7
- 238000002156 mixing Methods 0.000 claims description 27
- 239000000203 mixture Substances 0.000 claims description 23
- GWEVSGVZZGPLCZ-UHFFFAOYSA-N Titan oxide Chemical compound O=[Ti]=O GWEVSGVZZGPLCZ-UHFFFAOYSA-N 0.000 claims description 20
- 238000002310 reflectometry Methods 0.000 claims description 18
- 239000011248 coating agent Substances 0.000 claims description 16
- 238000000576 coating method Methods 0.000 claims description 16
- 239000000126 substance Substances 0.000 claims description 14
- 230000031700 light absorption Effects 0.000 claims description 10
- 239000004408 titanium dioxide Substances 0.000 claims description 10
- 230000014509 gene expression Effects 0.000 claims description 7
- 238000002360 preparation method Methods 0.000 claims description 7
- 238000000985 reflectance spectrum Methods 0.000 claims description 6
- 238000000149 argon plasma sintering Methods 0.000 claims description 5
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- 238000013461 design Methods 0.000 abstract description 8
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- WLDHEUZGFKACJH-UHFFFAOYSA-K amaranth Chemical compound [Na+].[Na+].[Na+].C12=CC=C(S([O-])(=O)=O)C=C2C=C(S([O-])(=O)=O)C(O)=C1N=NC1=CC=C(S([O-])(=O)=O)C2=CC=CC=C12 WLDHEUZGFKACJH-UHFFFAOYSA-K 0.000 description 4
- QFFVPLLCYGOFPU-UHFFFAOYSA-N barium chromate Chemical compound [Ba+2].[O-][Cr]([O-])(=O)=O QFFVPLLCYGOFPU-UHFFFAOYSA-N 0.000 description 4
- XCJYREBRNVKWGJ-UHFFFAOYSA-N copper(II) phthalocyanine Chemical compound [Cu+2].C12=CC=CC=C2C(N=C2[N-]C(C3=CC=CC=C32)=N2)=NC1=NC([C]1C=CC=CC1=1)=NC=1N=C1[C]3C=CC=CC3=C2[N-]1 XCJYREBRNVKWGJ-UHFFFAOYSA-N 0.000 description 4
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- CLOMYZFHNHFSIQ-UHFFFAOYSA-N clonixin Chemical compound CC1=C(Cl)C=CC=C1NC1=NC=CC=C1C(O)=O CLOMYZFHNHFSIQ-UHFFFAOYSA-N 0.000 description 1
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- 238000000295 emission spectrum Methods 0.000 description 1
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- 238000004088 simulation Methods 0.000 description 1
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Abstract
The invention discloses a computer-assisted same-color same-spectrum paint color matching method, and belongs to the technical field of camouflage design. The method comprises the following steps: establishing a basic pigment database: establishing spectral data of a plurality of pigments at different concentrations; establishing a two-parameter calculation model: establishing an optical model based on an absorption coefficient and a scattering coefficient; establishing a full spectrum color matching model: in the full wavelength range, the fitting spectral curve is consistent with the target spectral curve; solving by a dual simple line method: and fitting the optimal spectral curve and the pigment proportion thereof by adopting a dual pure line method. The invention realizes the effect of 'same color and same spectrum' of the matched color and the background color by the technical means of computer simulation color matching.
Description
Technical Field
The invention discloses a computer-assisted same-color same-spectrum paint color matching method, and belongs to the technical field of camouflage design.
Technical Field
Camouflage painting or other materials are mainly used for coating the surface of equipment with camouflage paint or other materials, are used for changing the surface spectral characteristics of the equipment, achieve the purposes of reducing the significance or distortion of a target and segmenting the outline of the target, and are mainly used for resisting the observation of visible light near infrared wave bands, photographing, multispectral imaging reconnaissance, guidance attack and the like. The camouflage design principle is that the color, brightness and the like of a part of spots are fused with the background to become a part of the background.
Most camouflage paints can only achieve the color of the visible light wave band consistent with the background color. However, the new generation of camouflage paint must meet the requirement of the consistency of the reflection spectrum and reach the performance index of 'same color and same spectrum'. The design method of the camouflage paint formula comprises a manual test method and a computer design method. The manual test method is a traditional color matching method, the method depends on personal experience to a great extent, formulas with similar colors can be obtained through hundreds of times of debugging, and the phenomenon of metamerism is easy to occur. The requirements of the camouflage paint on the color are very strict, and a paint film and a background have very similar reflection spectrum characteristics under different illumination conditions or multi-spectrum observation. Therefore, the color of the paint film is required to be consistent with that of the background environment, and the similarity of the reflection spectra of the paint film in visible and near infrared bands is also required to be correspondingly strict. Along with the rapid increase of the demand of the same-color and same-spectrum paint on color matching, the precision requirement is higher and higher, the manual color matching can not meet the demand due to the problems of low efficiency, poor precision and the like, and a computer color matching system is produced accordingly. The existing inorganic and organic pigment systems can be adopted, and the effect of 'same color and same spectrum' of the matched color and the background color is achieved by a technical means of full-spectrum simulation color matching.
Disclosure of Invention
The purpose of the invention is: a computer-aided same-color and same-spectrum paint color matching method is provided to improve the color matching efficiency and meet the same-color and same-spectrum precision requirement of the matched colors.
The technical scheme of the invention is as follows:
a computer-aided same-color same-spectrum paint color matching method is characterized by comprising the following steps:
(ii) base pigment database establishment
Mixing the reference color paste and other pigment color pastes according to different proportions to obtain mixed color samples with different concentrations, and measuring optical parameters and spectral data of the mixed color samples as basic data of the pigment in a basic pigment database;
the basic database is established by the following steps:
(1) color sample configuration;
(2) measuring the reflection spectrum r of each group of mixed color samples by adopting an ultraviolet visible spectrophotometeriWherein r represents the reflectance spectrum, i represents the pigment type, riRepresenting the reflectance spectra of different pigments;
(3) establishing a database of spectra of each pigment;
based on the Kubelka-Munk principle, for a reference color sample, an arbitrary color sample and a mixed color sample, a scattering coefficient relational expression under a certain wavelength is shown as a formula (1):
wherein S0Is the scattering coefficient of a standard colour sample, SiScattering coefficient, S, for arbitrary colour samplesmIs the scattering coefficient of the mixed color sample,
λ is wavelength, R is reflectance, S is scattering coefficient, K is absorption coefficient, C0Is the concentration of a standard colour sample, CiThe concentration of the arbitrary color paste i is obtained, so that the scattering coefficient S of the arbitrary color paste i under a certain wavelength when the concentration is mi(ii) a And a data set (i, m, lambda, R) is establishedi，Φi，Si，Ki)；
(II) double-parameter calculation model establishment
Calculating based on a Kubelka-Munk principle, and explaining the optical characteristics of the coating by using two parameters of a scattering coefficient S and an absorption coefficient K of the pigment; when incident light enters the pigment coating, the pigment coating can generate light scattering and light absorption; after different pigments are mixed, if the pigments do not play a chemical role, the absorption and scattering coefficients of the mixture conform to the principle of optical superposition of the pigments, namely the absorption and scattering coefficients of the mixture are the linear sum of the absorption and scattering coefficients of the pigments forming the mixture;
the conversion relation between the spectral reflectance of the mixed pigment and the composition ratio of the mixed pigment is shown in formula (2):
wherein K and S are the light absorption coefficient and the scattering coefficient of n pigments mixed according to the proportion under a certain wavelength, C1、C2...CnIs a mixture ratio of n pigments, KnAnd SnIs the absorption coefficient and scattering coefficient of the nth pigment, R is the reflectance;
(III) full spectrum color matching model establishment
The color of the object depends on the reflection spectrum, the reflection spectrum of the matched color sample is consistent with the reflection spectrum of the standard sample through computer simulation, and the color of the object and the color of the standard sample are certain identical, so that the same color and spectrum performance is achieved. That is, at a wavelength λ, there are: r allowing for standard sampleλ sWith R of the complexλ mThere is a certain difference Δ R betweenλIf the difference can be minimized and is within an acceptable range, the match is satisfactory. The spectral reflectance difference relationship between the matched sample and the standard sample is shown in formula (3):
wherein the content of the first and second substances,
is the reflectivity of the standard sample and is,
reflectance of the sample;
based on the Kubelka-Munk principle, the spectral reflectivity difference relationship between the matched sample and the standard sample is shown as a formula (4):
wherein the content of the first and second substances,
C1...Cnis the mixing proportion of n pigments;
with AλIs represented by the formulaiIndependent constants, using BλiIs represented by the formulaiThe correlation coefficient, the relationship between the spectral reflectance difference Δ R between the standard sample and the mixing ratio of each pigment, becomes a linear relationship as shown in equation (5):
ΔRλ＝Aλ+C1Bλ1+C2Bλ2+…+CnBλn (5)
wherein the content of the first and second substances,
solving by (IV) dual simplex line method
The full spectrum is divided by step length delta lambda to obtain the spectrum reflectivity difference delta R under n groups of wavelengthsn＝An+C1Bn1+C2Bn2+…+CiBniEquation (6), namely, the optimal value problem can be solved by converting the equation into linear programming;
iterative calculation is carried out by using a dual simple line method, an optimal value is solved, the minimum delta R can be met, and a formula of a sample preparation can be obtained;
the spectral reflectance difference minimization equation is as follows:
wherein A isλIs represented by the formulaiIndependent constant, BλiIs represented by the formulaiThe coefficients are related, C represents the pigment concentration, i represents the pigment type, CiRepresenting the concentrations of different pigments to finally obtain the optimal pigment ratio C1...CiAnd adding a normalization equation: c1+C2+…+Cn＝1。
When the basic pigment database is established in the step (I), optical basic data of a plurality of pigments can be established according to color matching requirements so as to ensure the accuracy of color matching. When color matching is calculated, a linear interpolation method is adopted to calculate the scattering coefficient and the absorption coefficient of any pigment under any concentration;
the basic pigment adopted in the step (3) in the step (I) is titanium dioxide color paste, and S can be directly made01, the scattering coefficient Si of any color paste can be obtained, and the unknown quantity Si/Sλ sI.e. becomes measurable, wherein
The existence of the scattering coefficient is equivalent to that each scattering coefficient is divided by one coefficient, and the finally solved mixing proportion of each pigment is not influenced;
step (III) is that the spectral reflectivity difference Delta R between the standard sample and the matched sample and the linear relation formula of the mixing ratio of each pigment are S1λ/Sλ S、...Snλ/Sλ SAs unknowns, the calculation of these unknowns is accomplished by the establishment of a base pigment database;
when the dual simple line method in the step (four) is used for solving the solution of the equation set, the method can be used for solving the solution of the equation set
Back substitution into BλiAnd increasing the solving precision.
And taking white paste as reference color paste.
And taking titanium dioxide color paste as reference color paste.
And (3) carrying out color sample preparation on the reference color paste and other pigment color pastes according to the following table:
the invention has the advantages that:
1. compared with an artificial color matching method, the computer-aided color matching method has the advantages that the method does not depend on personal experience in a transition way, the color matching is accurate, the efficiency is high, and the matched color and the target color have the characteristics of same color and same spectrum.
2. The invention adopts a double-parameter calculation model and a full spectrum color matching model, the matched color and the target color have the same color and spectrum characteristics, the spectral similarity of the two colors reaches more than 0.8, and the chromatic aberration is less than 2.
3. The computer-assisted same-color same-spectrum paint color matching method provided by the invention has high consistency between the matched color and the target color, can provide reference for the camouflage design of various environments, and is also suitable for the design of camouflage patterns of military targets under various different terrain backgrounds.
Drawings
FIG. 1 is a block diagram of a computer-aided co-chromatic co-spectral paint color matching method according to the present invention;
FIG. 2 is a graph of green background color and paint color emission spectra data in an example of the present invention;
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
A computer-aided same-color same-spectrum paint color matching method comprises the following steps:
(ii) base pigment database establishment
Mixing the reference color paste and other pigment color pastes according to different proportions to obtain mixed color samples with different concentrations, and measuring optical parameters and spectral data of the mixed color samples as basic data of the pigment in a basic pigment database;
the basic database is established by the following steps:
(1) color sample configuration;
(2) measuring the reflection spectrum r of each group of mixed color samples by adopting an ultraviolet visible spectrophotometeriWherein r represents the reflectance spectrum, i represents the pigment type, riRepresenting the reflectance spectra of different pigments;
(3) establishing a database of spectra of each pigment;
based on the Kubelka-Munk principle, for a reference color sample, an arbitrary color sample and a mixed color sample, a scattering coefficient relational expression under a certain wavelength is shown as a formula (1):
wherein S0Is the scattering coefficient of a standard colour sample, SiScattering coefficient, S, for arbitrary colour samplesmIs the scattering coefficient of the mixed color sample,
λ is wavelength, R is reflectance, S is scattering coefficient, K is absorption coefficient, C0Is the concentration of a standard colour sample, CiThe concentration of the arbitrary color paste i is obtained, so that the scattering coefficient S of the arbitrary color paste i under a certain wavelength when the concentration is mi(ii) a And a data set (i, m, lambda, R) is establishedi，Φi，Si，Ki)；
(II) double-parameter calculation model establishment
Calculating based on a Kubelka-Munk principle, and explaining the optical characteristics of the coating by using two parameters of a scattering coefficient S and an absorption coefficient K of the pigment; when incident light enters the pigment coating, the pigment coating can generate light scattering and light absorption; after different pigments are mixed, if the pigments do not play a chemical role, the absorption and scattering coefficients of the mixture conform to the principle of optical superposition of the pigments, namely the absorption and scattering coefficients of the mixture are the linear sum of the absorption and scattering coefficients of the pigments forming the mixture;
the conversion relation between the spectral reflectance of the mixed pigment and the composition ratio of the mixed pigment is shown in formula (2):
wherein K and S are the light absorption coefficient and the scattering coefficient of n pigments mixed according to the proportion under a certain wavelength, C1、C2...CnIs a mixture ratio of n pigments, KnAnd SnIs the absorption coefficient and scattering coefficient of the nth pigment, R is the reflectance;
(III) full spectrum color matching model establishment
The color of the object depends on the reflection spectrum, the reflection spectrum of the matched color sample is consistent with the reflection spectrum of the standard sample through computer simulation, and the color of the object and the color of the standard sample are certain identical, so that the same color and spectrum performance is achieved. That is, at a wavelength λ, there are: r allowing for standard sampleλ sWith R of the complexλ mThere is a certain difference Δ R betweenλIf the difference can be minimized and is within an acceptable range, the match is satisfactory. The spectral reflectance difference relationship between the matched sample and the standard sample is shown in formula (3):
wherein the content of the first and second substances,
is the reflectivity of the standard sample and is,
reflectance of the sample;
based on the Kubelka-Munk principle, the spectral reflectivity difference relationship between the matched sample and the standard sample is shown as a formula (4):
wherein the content of the first and second substances,
C1...Cnis the mixing proportion of n pigments;
with AλIs represented by the formulaiIndependent constants, using BλiIs represented by the formulaiThe correlation coefficient, the relationship between the spectral reflectance difference Δ R between the standard sample and the mixing ratio of each pigment, becomes a linear relationship as shown in equation (5):
ΔRλ＝Aλ+C1Bλ1+C2Bλ2+…+CnBλn (5)
wherein the content of the first and second substances,
solving by (IV) dual simplex line method
The full spectrum is divided by step length delta lambda to obtain the spectrum reflectivity difference delta R under n groups of wavelengthsn＝An+C1Bn1+C2Bn2+…+CiBniEquation (6), namely, the optimal value problem can be solved by converting the equation into linear programming;
iterative calculation is carried out by using a dual simple line method, an optimal value is solved, the minimum delta R can be met, and a formula of a sample preparation can be obtained;
the spectral reflectance difference minimization equation is as follows:
wherein A isλIs represented by the formulaiIndependent constant, BλiIs represented by the formulaiThe coefficients are related, C represents the pigment concentration, i represents the pigment type, CiRepresenting the concentrations of different pigments to finally obtain the optimal pigment ratio C1...CiAnd adding a normalization equation: c1+C2+…+Cn＝1。
When the basic pigment database is established in the step (I), optical basic data of a plurality of pigments can be established according to color matching requirements so as to ensure the accuracy of color matching. When color matching is calculated, a linear interpolation method is adopted to calculate the scattering coefficient and the absorption coefficient of any pigment under any concentration;
the basic pigment adopted in the step (3) in the step (I) is titanium dioxide color paste, and S can be directly made01, the scattering coefficient S of any color paste can be obtainediUnknown quantity Si/Sλ sI.e. becomes measurable, wherein
The existence of the scattering coefficient is equivalent to that each scattering coefficient is divided by one coefficient, and the finally solved mixing proportion of each pigment is not influenced;
step (III) is that the spectral reflectivity difference Delta R between the standard sample and the matched sample and the linear relation formula of the mixing ratio of each pigment are S1λ/Sλ s、...Snλ/Sλ sAs unknowns, the calculation of these unknowns is accomplished by the establishment of a base pigment database;
when the dual simple line method in the step (four) is used for solving the solution of the equation set, the method can be used for solving the solution of the equation set
Back substitution into BλiAnd increasing the solving precision.
And taking white paste as reference color paste.
And taking titanium dioxide color paste as reference color paste.
And (3) carrying out color sample preparation on the reference color paste and other pigment color pastes according to the following table:
a computer-aided same-color same-spectrum paint color matching method is characterized by comprising the following steps:
s01, establishing a basic pigment database;
the method comprises the steps of taking titanium dioxide color paste (white paste) as a reference color paste, mixing any pigment color paste with the white paste according to different proportions to obtain mixed color samples under several levels of concentration, and measuring optical parameters and spectral data of the mixed color samples to serve as basic data of the pigment in a basic pigment database.
The basic database is established by the following steps:
s01.1, color sample configuration;
color samples were prepared according to the mass ratio of the mixed color samples shown in Table 1.
TABLE 1 quality ratio of color-mixed color sample for basic database
S01.2 measuring the reflection spectrum R of each group of mixed color samples by adopting an ultraviolet visible light spectrophotometeri；
S01.3, establishing a spectrum database of each pigment;
the following expressions are respectively given for a reference color sample, an arbitrary color sample and a mixed color sample at a certain wavelength:
based on the Kubelka-Munk principle, the scattering coefficient relational expression for the reference color sample, the arbitrary color sample and the mixed color sample is as follows:
S0the scattering coefficient of a standard color sample;
Sithe scattering coefficient of any color sample;
Smthe scattering coefficient of the mixed color sample is shown;
λ is wavelength, R is reflectance, S is scattering coefficient, K is absorption coefficient, and C is concentration;
thus obtaining the scattering coefficient S of any color paste i under a certain wavelength when the concentration is mi. Establishing a data set (i, m, lambda, R)i，Φi，Si，Ki)；
S02, establishing a double-parameter calculation model;
the calculation is carried out based on the Kubelka-Munk principle, and the optical characteristics of the coating are explained by two parameters of the scattering coefficient S and the absorption coefficient K of the pigment. When incident light enters the pigment coating, the pigment coating will undergo light scattering and light absorption. After different pigments are mixed, if the pigments do not play a chemical role, the absorption and scattering coefficients of the mixture conform to the principle of optical superposition of the pigments, namely the absorption and scattering coefficients of the mixture are the linear sum of the absorption and scattering coefficients of the pigments forming the mixture;
the conversion relation between the spectral reflectance of the mixed pigment and the composition ratio of the mixed pigment is as follows:
whereinK and S are the light absorption coefficient and the scattering coefficient of n pigments at a certain wavelength after being mixed according to the proportion; c1、C2...CnIs the mixing proportion of n pigments; knAnd SnIs the absorption coefficient and scattering coefficient of the nth pigment;
s03, establishing a full-spectrum color matching model;
the color of the object depends on the reflection spectrum, the reflection spectrum of the matched color sample is consistent with the reflection spectrum of the standard sample through computer simulation, and the color of the object and the color of the standard sample are certain identical, so that the same color and spectrum performance is achieved. That is, at a wavelength λ, there are: r allowing for standard sampleλ sWith R of the complexλ mThere is a certain difference Δ R betweenλIf the difference can be minimized and is within an acceptable range, the match is satisfactory. The spectral reflectance difference between the matched sample and the standard sample is as follows:
based on the Kubelka-Munk principle, the spectral reflectivity difference relation between the matched sample and the standard sample is as follows:
in the above formula C1...CnIs the mixing proportion of n pigments. If used with AλIs represented by the formulaiIndependent constants withBλiIs represented by the formulaiThe correlation coefficient, the difference in spectral reflectance Δ R between the standard and the sample, and the mixing ratio of each pigment, became linear as follows:
ΔRλ＝Aλ+C1Bλ1+C2Bλ2+…+CnBλn (5)
different sets of linear equations are available for different wavelengths. Plus the normalization equation:
C1+C2+…+Cn＝1；
s04, solving by a dual simple line method;
the full spectrum is divided by step length delta lambda to obtain the spectrum reflectivity difference delta R under n groups of wavelengthsn＝An+C1Bn1+C2Bn2+…+CiBniNamely n sets of equations in the formula (6). The method can be converted into a linear programming method to solve the optimal value problem;
iterative calculation is carried out by using a dual simple line method, an optimal value is solved, the minimum delta R can be met, and a formula of a sample preparation can be obtained;
the spectral reflectance difference minimization equation is as follows:
obtaining the optimal pigment ratio C1...Ci；
Further: when the basic pigment database is established in step S01, optical basic data of a plurality of pigments can be established according to color matching requirements to ensure accuracy of color matching. When color matching is calculated, a linear interpolation method is adopted to calculate the scattering coefficient and the absorption coefficient of any pigment under any concentration;
further: the basic pigment adopted in the step S01.3 is titanium dioxide color paste,can directly order S 01, the scattering coefficient S of any color paste can be obtainediMiddle, unknown quantity Si/Sλ sI.e. becomes measurable, wherein
The existence of the scattering coefficient is equivalent to that each scattering coefficient is divided by one coefficient, and the finally solved mixing proportion of each pigment is not influenced;
further: s03 step, the difference of spectral reflectivity DeltaR between the standard sample and the matched sample and the linear relation of each pigment mixing ratio1λ/Sλ S、...Snλ/Sλ SAs unknowns, the calculation of these unknowns is accomplished by the establishment of a base pigment database;
further: when the dual simple-row method of step S04 is used to solve the solution of the equation set, the method may be used
Back substitution into BλiAnd increasing the solving precision.
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
A computer-aided same-color same-spectrum paint color matching method comprises the following steps:
s01, establishing a basic pigment database;
the method comprises the steps of taking titanium dioxide color paste (white paste) as a reference color paste, mixing any pigment color paste with the white paste according to different proportions to obtain mixed color samples under several levels of concentration, and measuring optical parameters and spectral data of the mixed color samples to serve as basic data of the pigment in a basic pigment database. Carbon black, phthalocyanine blue, permanent yellow and fast red pigments are selected.
The basic database is established by the following steps:
s01.1, color sample configuration;
color samples were prepared according to the mass ratio of the mixed color samples shown in Table 2.
TABLE 2 quality ratio of color-mixed color sample for basic database
S01.2 measuring the reflection spectrum R of each group of mixed color samples by adopting an ultraviolet visible light spectrophotometeri；
S01.3, establishing a spectrum database of each pigment;
the following expressions are respectively given for a reference color sample, an arbitrary color sample and a mixed color sample at a certain wavelength:
based on the Kubelka-Munk principle, the scattering coefficient relational expression for the reference color sample, the arbitrary color sample and the mixed color sample is as follows:
S0the scattering coefficient of a standard color sample;
Sithe scattering coefficient of any color sample;
Smthe scattering coefficient of the mixed color sample is shown;
λ is wavelength, R is reflectance, S is scattering coefficient, K is absorption coefficient, and C is concentration;
thus obtaining the scattering coefficient S of any color paste i under a certain wavelength when the concentration is mi. Establishing a data set (i, m, lambda, R)i，Φi，Si，Ki)；
And collecting spectral reflection data of phthalocyanine blue, permanent yellow and fast red pigments according to the same steps, and establishing basic data of various pigments to ensure the accuracy of color matching. When color matching is calculated, a linear interpolation method is adopted to calculate the scattering coefficient and the absorption coefficient of any pigment under any concentration;
the basic pigment adopted in the step S01.3 is titanium dioxide color paste, and S can be directly made01, the scattering coefficient S of any color paste can be obtainediUnknown quantity Si/Sλ sI.e. becomes measurable, wherein
The existence of the scattering coefficient is equivalent to that each scattering coefficient is divided by one coefficient, and the finally solved mixing proportion of each pigment is not influenced;
taking the data of carbon black at a wavelength of 380nm as an example:
TABLE 3 data Table of basic pigments for carbon black pigments at a wavelength of 380nm
Inputting spectral reflectance data of carbon black with the wavelength of 380-780 nm and the step length of 5 nm;
inputting spectral reflectance data of phthalocyanine blue, permanent yellow and fast red pigments with the wavelength of 380-780 nm and the step length of 5 nm;
s02, establishing a double-parameter calculation model;
the calculation is carried out based on the Kubelka-Munk principle, and the optical characteristics of the coating are explained by two parameters of the scattering coefficient S and the absorption coefficient K of the pigment. When incident light enters the pigment coating, the pigment coating will undergo light scattering and light absorption. After different pigments are mixed, if the pigments do not play a chemical role, the absorption and scattering coefficients of the mixture conform to the principle of optical superposition of the pigments, namely the absorption and scattering coefficients of the mixture are the linear sum of the absorption and scattering coefficients of the pigments forming the mixture;
the conversion relation between the spectral reflectance of the mixed pigment and the composition ratio of the mixed pigment is as follows:
k and S are the light absorption coefficient and the scattering coefficient of n pigments mixed according to the proportion under a certain wavelength; c1、C2...CnIs the mixing proportion of n pigments; knAnd SnIs the absorption coefficient and scattering coefficient of the nth pigment;
s03, establishing a full-spectrum color matching model;
the color of the object depends on the reflection spectrum, the reflection spectrum of the matched color sample is consistent with the reflection spectrum of the standard sample through computer simulation, and the color of the object and the color of the standard sample are certain identical, so that the same color and spectrum performance is achieved. That is, at a wavelength λ, there are: r allowing for standard sampleλ sWith R of the complexλ mThere is a certain difference Δ R betweenλIf the difference can be minimized and is within an acceptable range, the match is satisfactory. The spectral reflectance difference between the matched sample and the standard sample is as follows:
based on the Kubelka-Munk principle, the spectral reflectivity difference relation between the matched sample and the standard sample is as follows:
in the above formula C1...CnIs the mixing proportion of n pigments. If used with AλIs represented by the formulaiIndependent constants, using BλiIs represented by the formulaiThe correlation coefficient, the difference in spectral reflectance Δ R between the standard and the sample, and the mixing ratio of each pigment, became linear as follows:
ΔRλ＝Aλ+C1Bλ1+C2Bλ2+…+CnBλn (5)
different sets of linear equations are available for different wavelengths. Plus the normalization equation:
C1+C2+…+Cn＝1；
step S03 Linear relationship between spectral reflectance difference Δ R between standard and batch and the mixing ratio of each pigment1λ/Sλ S、...Snλ/Sλ SAs unknowns, the calculation of these unknowns is accomplished by the establishment of a base pigment database;
s04, solving by a dual simple line method;
the full spectrum is divided by step length delta lambda to obtain the spectrum difference delta R under n groups of wavelengthsn＝An+C1Bn1+C2Bn2+…+CiBniNamely n sets of equations in the formula (6). The method can be converted into a linear programming method to solve the optimal value problem;
iterative calculation is carried out by using a dual simple line method, an optimal value is solved, the minimum delta R can be met, and a formula of a sample preparation can be obtained;
the set of spectral difference minimization equations is as follows:
obtaining the optimal pigment ratio C1...Ci；；
When the dual simple-row method is used for solving the solution of the equation set in the step S04, the method is to
Back substitution into BλiAnd increasing the solving precision.
In the embodiment of the invention, the background color is medium green, and the pigment ratios after the operation of a computer-aided color matching program are shown in the following table 4:
the proportions of the green pigments in Table 4
| Pigment (I) | Ratio of |
| Carbon black | 12.10％ |
| Phthalocyanine blue | 8.86％ |
| Permanent yellow | 38.56％ |
| Fast red | 40.48％ |
In the embodiment of the invention, the background color is medium green, the spectral data of the color of the paint formula calculated by a computer-aided color matching program is shown in fig. 2, the consistency of the paint color and the background color is better, the spectral similarity is more than 0.9, the color difference is less than 2, and the paint color and the background color achieve the same color and the same spectrum.
The invention provides a computer-assisted same-color same-spectrum paint color matching method, and belongs to the technical field of camouflage design. Which comprises the following steps: s01 establishing a basic pigment database: establishing spectral data of a plurality of pigments at different concentrations; s02 two-parameter calculation model establishment: establishing an optical model based on an absorption coefficient and a scattering coefficient; s03, establishing a full spectrum color matching model: in the full wavelength range, the fitting spectral curve is consistent with the target spectral curve; s04 solution by dual simple line method: and fitting the optimal spectral curve and the pigment proportion thereof by adopting a dual pure line method. The invention realizes the effect of 'same color and same spectrum' of the matched color and the background color by the technical means of computer simulation color matching. The method and technical thought of the invention promote the development of the color matching technology and the related fields thereof.
The invention is not the best known technology.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (8)
1. A computer-aided same-color same-spectrum paint color matching method is characterized by comprising the following steps:
(ii) base pigment database establishment
Mixing the reference color paste and other pigment color pastes according to different proportions to obtain mixed color samples with different concentrations, and measuring optical parameters and spectral data of the mixed color samples as basic data of the pigment in a basic pigment database;
the basic database is established by the following steps:
(1) color sample configuration;
(2) measuring the reflection spectrum r of each group of mixed color samples by adopting an ultraviolet visible spectrophotometeriWherein r represents the reflectance spectrum, i represents the pigment type, riRepresenting the reflectance spectra of different pigments;
(3) establishing a database of spectra of each pigment;
based on the Kubelka-Munk principle, for a reference color sample, an arbitrary color sample and a mixed color sample, a scattering coefficient relational expression under a certain wavelength is shown as a formula (1):
wherein S0Is the scattering coefficient of a standard colour sample, SiScattering coefficient, S, for arbitrary colour samplesmIs the scattering coefficient of the mixed color sample,
λ is wavelength, R is reflectance, S is scattering coefficient, K is absorption coefficient, C0Is the concentration of a standard colour sample, CiThe concentration of the arbitrary color paste i is obtained, so that the scattering coefficient S of the arbitrary color paste i under a certain wavelength when the concentration is mi(ii) a And a data set (i, m, lambda, R) is establishedi，Φi，Si，Ki)；
(II) double-parameter calculation model establishment
Calculating based on a Kubelka-Munk principle, and explaining the optical characteristics of the coating by using two parameters of a scattering coefficient S and an absorption coefficient K of the pigment; when incident light enters the pigment coating, the pigment coating can generate light scattering and light absorption; after different pigments are mixed, if the pigments do not play a chemical role, the absorption and scattering coefficients of the mixture conform to the principle of optical superposition of the pigments, namely the absorption and scattering coefficients of the mixture are the linear sum of the absorption and scattering coefficients of the pigments forming the mixture;
the conversion relation between the spectral reflectance of the mixed pigment and the composition ratio of the mixed pigment is shown in formula (2):
wherein K and S are the light absorption coefficient and the scattering coefficient of n pigments mixed according to the proportion under a certain wavelength, C1、C2…CnIs a mixture ratio of n pigments, KnAnd SnIs the absorption coefficient and scattering coefficient of the nth pigment, R is the reflectance;
(III) full spectrum color matching model establishment
The color of the object depends on the reflection spectrum, the reflection spectrum of the matched color sample is consistent with the reflection spectrum of the standard sample through computer simulation, and the color of the object and the color of the standard sample are certain identical, so that the same color and spectrum performance is achieved. That is, at a wavelength λ, there are: r allowing for standard sampleλ sWith R of the complexλ mThere is a certain difference Δ R betweenλIf the difference can be minimized and is within an acceptable range, the match is satisfactory. The spectral reflectance difference relationship between the matched sample and the standard sample is shown in formula (3):
wherein the content of the first and second substances,
is the reflectivity of the standard sample and is,
reflectance of the sample;
based on the Kubelka-Munk principle, the spectral reflectivity difference relationship between the matched sample and the standard sample is shown as a formula (4):
wherein the content of the first and second substances,
C1…Cnis the mixing proportion of n pigments;
with AλIs represented by the formulaiIndependent constants, using BλiIs represented by the formulaiThe correlation coefficient, the relationship between the spectral reflectance difference Δ R between the standard sample and the mixing ratio of each pigment, becomes a linear relationship as shown in equation (5):
ΔRλ＝Aλ+C1Bλ1+C2Bλ2+…+CnBλn (5)
wherein the content of the first and second substances,
solving by (IV) dual simplex line method
The full spectrum is divided by step length delta lambda to obtain the spectrum reflectivity difference delta R under n groups of wavelengthsn＝An+C1Bn1+C2Bn2+…+CiBniEquation (6), namely, the optimal value problem can be solved by converting the equation into linear programming;
iterative calculation is carried out by using a dual simple line method, an optimal value is solved, the minimum delta R can be met, and a formula of a sample preparation can be obtained;
the spectral reflectance difference minimization equation is as follows:
wherein A isλIs represented by the formulaiIndependent constant, BλiIs represented by the formulaiThe coefficients are related, C represents the pigment concentration, i represents the pigment type, CiRepresenting the concentrations of different pigments to finally obtain the optimal pigment ratio C1…CiAnd adding a normalization equation: c1+C2+…+Cn＝1。
2. The computer-aided metameric paint color matching method according to claim 1, characterized in that: when the basic pigment database is established in the step (I), optical basic data of a plurality of pigments can be established according to color matching requirements so as to ensure the accuracy of color matching. When the color matching is calculated, the scattering coefficient and the absorption coefficient of any pigment under any concentration can be calculated by adopting a linear interpolation method.
3. The computer-aided metameric paint color matching method according to claim 1, characterized in that: the basic pigment adopted in the step (3) in the step (I) is titanium dioxide color paste, and S can be directly made01, the scattering coefficient S of any color paste can be obtainediUnknown quantity Si/Sλ sI.e. becomes measurable, wherein
The existence of the scattering coefficient is equivalent to the same division of each scattering coefficient by one coefficient, and does not influence the mixing ratio of each pigment obtained by final solution.
4. The computer-aided metameric paint color matching method according to claim 1, characterized in that: step (III) is that the spectral reflectivity difference Delta R between the standard sample and the matched sample and the linear relation formula of the mixing ratio of each pigment are S1λ/Sλ S、…Snλ/Sλ SFor unknown quantities, the calculation of these unknown quantities is carried out by the establishment of a base pigment database.
5. The computer-aided metameric paint color matching method according to claim 1, characterized in that: when the dual simple line method in the step (four) is used for solving the solution of the equation set, the method can be used for solving the solution of the equation set
Back substitution into BλiAnd increasing the solving precision.
6. The computer-aided metamerism paint color matching method according to claim 1, wherein white paste is used as a reference color paste.
7. The computer-aided metamerism paint color matching method according to claim 1, wherein a titanium dioxide color paste is used as a reference color paste.
8. The computer-aided metamerism paint color matching method according to claim 1, wherein the reference color paste and other pigment color pastes are arranged according to the following table.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102729612A (en) * | 2012-06-27 | 2012-10-17 | 杭州电子科技大学 | Multi-target optimization and color-matching method of special-color ink in offset printing |
| CN105667069A (en) * | 2016-03-08 | 2016-06-15 | 西安理工大学 | Spectral color matching method based on Berr-Lambert's law |
| CN106469258A (en) * | 2016-09-28 | 2017-03-01 | 武汉大学 | A kind of colored fibre mixing color matching method theoretical based on double constant Kubelka Munk |
| CN107194081A (en) * | 2017-05-25 | 2017-09-22 | 魔金真彩网络科技（长沙）有限公司 | A kind of automobile plain color paint computer for colouring method |
| CN109582994A (en) * | 2018-07-30 | 2019-04-05 | 浙江理工大学上虞工业技术研究院有限公司 | A kind of colour-spun yarns Intelligent Selection color color matching method |
-
2021
- 2021-09-24 CN CN202111119863.7A patent/CN113976037A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102729612A (en) * | 2012-06-27 | 2012-10-17 | 杭州电子科技大学 | Multi-target optimization and color-matching method of special-color ink in offset printing |
| CN105667069A (en) * | 2016-03-08 | 2016-06-15 | 西安理工大学 | Spectral color matching method based on Berr-Lambert's law |
| CN106469258A (en) * | 2016-09-28 | 2017-03-01 | 武汉大学 | A kind of colored fibre mixing color matching method theoretical based on double constant Kubelka Munk |
| CN107194081A (en) * | 2017-05-25 | 2017-09-22 | 魔金真彩网络科技（长沙）有限公司 | A kind of automobile plain color paint computer for colouring method |
| CN109582994A (en) * | 2018-07-30 | 2019-04-05 | 浙江理工大学上虞工业技术研究院有限公司 | A kind of colour-spun yarns Intelligent Selection color color matching method |
Non-Patent Citations (1)
| Title |
|---|
| 李静等: "《迷彩伪装涂料的计算机辅助配色研究》", 《涂料工业》, vol. 37, no. 9, 31 December 2007 (2007-12-31), pages 18 - 24 * |
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