CA1221853A - Three direction measurements for characterization of a surface containing metallic particles - Google Patents

Abstract

TITLE
Three Direction Measurement For Characterization Of a Surface Containing Metallic particles ABSTRACT OF THE DISCLOSURE
An improved method for instrumentally characterizing the optical properties of a surface containing metallic particles such as a paint containing metallic flakes by using multiangular spectrophotanetric or colormetric measurements to derive color constants for the paint, wherein the improvement comprises using three multiangular measurements, preferably 15%, 45% and 110° as measured from the specular angle .

Description

~2Z~ii3 TXTL~
Three Direction Measurement For Characterization Of a Surface Containing Metallic Particles BACK~ROUND OF THE INVE~TION
5In the ~anufacture of pigmented f inishes one rarely if ever achieves a ~atisfactory color match versus ~ color standard without an adjustment process known as shading~ Shading usually involves a rela~ively minor but cri tical ~anipulation of the 10 formula pigment composition, correcting for the cumul~tive effects of manu~acturing variables on pigment dispersions.
Traditionally, the shading process has been c:arried out by highly skilled and tr~ined personnel 15 who require extensiv~ on-the-job experience to achieve proficiency in their craft. Since visual shading at best is an art, effective adrninistration of the process was difficult.
In more recent years, such visual shading 20 has been supplemented by the use of apparatuses for instrumentally characterizing ~ paint or pigment composi tion . Colorimeters and spectropho~ometers are well-known in the art and ~re used to measure certain optical properties of various paint films which have 2S been c3ated over test panels. A typical spectrophotometer provides for the measurement of the amount of light reflected at varying light wavelength in the visible spectrum by a painted panel that is held at a given angle relative to the di rection of an incident source of light. The reflectance factor of the paint en abl es pa i nt chem i s ts to cal cul at e col or values by which to characteri~e variou~ paint colors. For a paint containing no light-reflecting flakes or platelets (i.e., non-met~llic paints), the reflectance factor will not vary with the angle of ,, lZ21853 the panel relative to the direction of incident light except at the gloss (specular ) ~ngle. Consequently, a single cpectrophota~etric reading at any specif ied an~le will produce a reflectance value by which to 5 accur ately characteri ze the pai nt .
EIowever, the paint industry of ten util izes light reflecting flakes in pain~s (i.e., met~llic paints) ~o obtain pleasing aesthetic effects~ Paints containing Iight-reflecting flakes of such materials 10 as al~nin~o, bronze, ~oated mica and the like are charac~erized by a ~two-tone" or ~flip-flop" effect whereby the apparent o~lor of ~he paint changes at different viewing ~ngles. This effect is due to the orientation of the flakes in the paint film. 5ince 15 the e:olor of such met~llic paints will apparently vary as a func:tion of the angle of ill~nination and viewing, a s~ngle spectropho~canetric reading is inadequate to ~ccurately characterize the pain~.
Although measurement studies have chown th~t visual color differences existing between two metallic paints were detectable at an infinite n~nber of angles, it is obvlous that practical reasons preclude the collection of reflectance factors for an infinite number of vi.ewing angles. E~owever, previous studies have also indicated tha~ measurement of the optical properties of a metallic paint at only two specified angles can provide useful characterization. See, for example, U.S. Patent No. 3,690,771, issued September 12, 1972 to Armstrong, Jr., Edwards, Laird, ~nd Vining.

The present invention relates to the discovery that unexpectedly improved op~i~al characterization of metallic paint~ results when measure~ents are taken at three specif ied angles .

iZZ1853 S UMM;~ R Y OF T ~ I NVE NT I O~
-There is provided by the present invention an improved method for instr~nentally characterizing the optical properties of a surface containing 5 metallic particles such as paint-containing metallic par t i cl es or f l akes by us i ng mul ti angul ar spectrophotometri~ or colorimetric measurelT ents to derive color constarl~s for the paint, wherein th improvement comprises using three multiangular 10 measurements.
~RIEF D~S CRIPrrION OF DRA~INGS
FIGo 1 is a graphic representation of the angul ar dependence of tristimulus v~lues.
FIG. 2 is a schematic represen~ation of a preferred spectrophotometric system embodying the ~ethod of the present invention.
DETAILED DESCRIPTION OF THE INVENTION
_ .
In optically characterizing surfaces containing metallic particles such as ~etallic paints 20 and f ilms t it was recognized that directional reflectance had to be considered~ Metallic paints contain light-reflecting flakes or platelets of such materlal as al~ninum, bronze, coated mica and the like. These flakes or platelets function much like 25 little mirrors, reflecting light directionally rather than in a diffuse manner. The directional reflectance characteristic of ~ metallic paint f ilm result~ in a phencmenon known as goniochr~xnatism, which is def ined as the variation in ~:olor of a paint 30 film as a function of the directions of illumination ~nd viewing. This phenomenon is also sometimes descri~ed as ~two-tone", ~flop", ~flip-flop~, " flash", " side-tone", etc . In sum, the color of a ~net all ic pai nt will appe ar d i f ferent at d i f f er ent 35 viewing angles.

~Z2~ i3 To account for this directional or angular -reflectance, i.e, goniochromatism, spectrophotcmetrically determined reflec~ance factors must be taken multiangularly. The reflectance factor 5 of a paint f ilm is the ratio of the light flux reflected from the film sample to the light flux reflected frcm a perfect reflecting diffuser when the sample and perfect diffus er are identically irradiated. A per~ect white reflector has a value of 1. A perfect black nonreflector has a value of 0.
The reflectance factors are used to calculate color descriptor values used to specify color and color difference. The tristimulus values (X, Y, Z) of a color are calculated ~y combining the 15 reflectance factor data (R) with data on the sensitivity of the human eye ~x, y, z~ and the irradiance o~ ~ light source ~E) all as f unctions of wavelength (~) in the visible spectrum. The def ining equations f or t r i s timul us val ues 2~r e:
X =360J R (~.) E (A~ x (~) dA
y I R (~1 E (~.) y ~A) d~
z =3~;0~ R (~.) E ~) æ (~ ) dA
25 ~he tristimulus values can be used to ca:Lculate color descriptors which relate to visual perception o~
color and color difference. One of many sets of descriptors which can be used are the CIELAB
perceptual color scales recommended by the 30 International Commission on Illumination l"Recommendations on Uniform Color Spaces, Color Diff erence Equations , Psychanetric Color Terms", Supplement No. 2 To CIE Publication No. 15 (El.3.1) 1971/CTtl.3) 1978. Bureau Central De La CIE, 52, 35 Boulevard Malesherbes 750û8, Paris, France).
.

~ ZZ~153 Transformations of the tristimulus values can be used to calculate perceptual color values describing ligh~ness (I.*), redness/gr eenness (a~), yell~ness/blueness (b*), saturation ~C) or hue (H).
5 A color can be canpletely descri~ed by a set of L, a, b or L, C, ~ values. The following equations which have been specif ied by the I nternational Commi ttee on Ill~nination relate the tristimulus values to I.*, a~
and b*
L* - 116 (Y/Yc) 1/3 -16 a* s ~oo ~ (x/xo)l/3_(y/yo)lJ3 b* ~ 20~ ~ (y/yo)l/3-(z/zo)l/
where Xo, Yo and Zo are the tristimulus values of 15 the perfect white for a given illuminant;
X, Y and Z are the tristimulus values for the color.
The s at uration (C) and hue (~) descriptors are related to the a* and b* values as follows:
C _ (a*2 + b*2~1/2 ~ - ~an 1 (b~/a~1 Of~en it i5 necessary to compare a color such ~s a sample batch of paint to a standard color and determine the difference and then adjust ~he ~5 sample with appropriate additives to bring the sample within tolerance values of the standard. The difference in col~r between 8 color standard and a batch sample is described as f ollows:
~L* = L* (batchl - L* (standard) aa* = a* (batch) - a* (standard) ab* = b* (batch) - b* (standard~
The resultant values agree with the visual assessments of differences in lightness t~L*), redness/greenness (aa*3 and yellowness~blueness (ab*~.

~L2;Z1853 Further discussion will e~ploy the tristimulus values (X, Y, Z) and perceptual color values (L*, a*, b*, C, ~) to quantify the influence of changing conditions of illumination and viewing on measurement of goniochromatic color. The specific color descriptors employed are only one of many possible choices o transformations of tristimulus values which could be employed in this task.
The tristimulus values, anfl hence the L*, a*, b* values as well, for a metallic paint vary in a regular manner with regular variation in the angle of viewing the paint film. In FIG. 1, the directional color behavior of a solution lacquer medium red metallic color is shown. The sample was prepared by conventional air atomized spray onto an aluminum substrate followed by a 155C bake fnr 30 minutes.
Reflectance factor measurements relative to a standard white (BaS~4) were made in six sets of irradiation and viewing directions using a reflection spectrophotometer specif ically designed to measure reflection properties with Yariable measurement geometry. This instrument is esser.tially a standard spectrophotometer consist;ng of a lightsource, monochrometer, variable measurement geometry module, light detector and associated control and readout elect ron i cs . The reflectance factor for each measurement geometry was used to calculate tristimulus val ues as previously described. In FIG. 1, the angular dependence of tristimulus values, Xt Y and Z is illustrated. The angle is measured from the specular (or ~mirr2r~) angle.
The val~es used for FIG. 1 are as follows:

~2Z~8S3 Meas ur ement Angle Fran the Specular A~ 'C ' l T r i s t i m u 1. us V al ue s X Y
67.6 57.2 46.
~1.2 17.3 13.3 ~5 12.9 10.3 7.7 8~4 6.7 4.
7~ 5.0 3.9 2.6 3.6 2.8 1.9 An al ys i s of the an gu 1 ar de pe n de n ce pl ot of FIG. 1 reveals three things:
(1) Tristimulus values are not constant with angle variatiQn, hence values frcxn multiple angle measurements are necessary to accurately describe the color behavior of the sample;
(23 The plots are monotonically decreasing funct;ons as the angle from specular increases, therefore a simple mathematical model should describe the curve; and (3) The plots are curYed such that the ~athematical model should probably be one higher than of the ~irst ordee (linear).
Similar angular dependence plots have been 25 obtained for a wide variety of metallic colors and all show si~ilar results. The significance of these results is that they define the metallic color characteri zation and specif ication problem. Since all metallic colors show similar curved, monotomically decreasing tristimulus values as f unctions of the measurement di rection f rom the specular angle, there is A systematic angular color behavior for which ~ simple measurement strategy can be developed. Multiple measurements will be required 35 to adequately characterize this behavior.

1~2~1~S3 Since L~, a*, and b~ are the color values usually employed to characterize the color of paint f ilms, it is of prime importance ~Lo determine the number of measuremen~s neecled to satisfactorily 5 characteri ze the angular dependence of these values .
Plots of all three variables are adequately similar, ~o ~hat it is reasonable to ass~ne that a mathematical characterization that fit a plot of the angular dependence of L~ would also fit a plot of the 10 angular dependence of a* and b*.
The optimum f it of various mathematical models to a lightness (L*) angular dependence curve is of the seoond order, which requires three measurements.
This can be shown by considering the mean residual error in L* value at six sets of ~easuring directions as predicted by various prediction models employing subsets of the six measuring directions.
The reflectance factors in 6 measurement geometries for 37 solution lacquer metallic colors was de~ermined and the lightness values, L~, for these geometries calculated. The samples were prepared and measured as previously described. The objective is to define a metallic ~olor characterizatiQn system which provides optimum informat on for minimum effort. This is done by considering whether subsets of the ~ measurement geometry data are adequate to predict the color lightness behavior at all 6 geometries. A linear metallic color chara~terization model are developed based on a first order equation. S~ch equations for the angular dependence of metallic lightness have the form:
~L al + a2~
where L* is lig'ntness, ~ is angle from the specular ansle and al and a2 are constants specif ic to each color which are fit frcm measurements uslng at least two different measurement directions.
Similarly, a q~adratic (second order~ equation is 5 used havi ng the f orm:
*L = al + a2 ~ + a3~
where the variables are the same as in the linear example with the addition of another constant a3.
A minim~n of three measurement directions are now required. Table I indicates the mean sum o~ squares residual for 6 measurement geometries with 37 metallic colors with several metallic characteri zation models. When the mean sum at squares residual is low, a model which describes the color dependence of metallic color on measurement direction has been formed.
TABLE
Influence of measurement direction selection on metallic color lightness prediction.
Number of Mean Sum of Squares Model ~easurement Residual for 6 Measurement (OrderL Directions_ Directions.
Linear (1) 2 529.3 Quadratic (2) 3 12.5

2 5 n 4 ~j 8.5 Addition of just one more measurement, taken nearer to the specular angle, decreases the sum of the squares error of prediction from 529.3 ~o 12.5 in L* units. This indicates that the metallic color lightness behavior at any direc~ion can be well predicted from measureme~ts at 3 selected directions.
~ igher accuracy can be achieved by adding more measure~ent angles or by going to a higher order

3~ equation with more measurement angles, but no such ~L2Z1~3 move will lead to the dramatic and ~urprisin~
increase in accuracy at~ainable by u~ ing a ~econd order m~del incorporating ~ust on~ mOe angle measurement than in the ~-angle ~ystem. Th~c is, 5 three properly selected measurement diect.ions are ~n optimized ~election ~o give m~xim~n information on metallic color fol minim~n measurement efort. The example da~a ~escribe the optir~i ~atiion results for lightness values. Si~ilar results are o~tained for 10 tristimulus value~ ~X, Y, Z~, perceptual ccllor ~ralues S~*? b~ , El) f color difference values 5~L*t ~a*l ~b*) or other transformation fxom tristimulus ~alues.
In oollecting dat~ on the opti csl characterlzation of ~ paint film, e ~rariety of 15 measur~nent techni~ues can be used. One technique is object modulated reflectance (O~) wherein the light source and viewer or detector reference point are f ixed and the object position i5 varied. This techni~ue is exemplified in U.~. Patent No.
20 .3,712,745, issued January 23, lg73 to Armstrong, Jr., E dwar ds, and Yi ni ng.
Two other techniques are Detector P~odulated Reflectance IDMR3 and Illuminant Modulated Re~lectance (IMR). In ~ he detector is varied while the light source and object are fixed. And in IM~r ~he lll~inant or light source i~ varied, while detector and object remain ~ixed.
As discussed earlier, analysis o~ data tcollected by use of DMR) ~ndic~ted that the optimum 30 set of ~neasurements to characterize the goniochrosnati~ effect in metallic paint f ilms ~onsists of measurements Saken at three angles: tl) near the ~pecular angle; (2) ~bout 4S fraTI the ular angle; and (3) f ar f rom the specular angle .
35 In gener~l, f~r a ~yp~cal metallic color~ the angular ~0 dDpendence of L*, C, H values is of the second order for any set of anqles varying regularly from near specular to far from specular/ whether measured by OMR, DMR, IMR or some co~bination of these~ Hence, 5 whether OMR, DMR, or IMR is utili zed, three measurements can optimally characterize the L*, ~, H
angular dependence curves.
FIG. ~ represents a preferred embodiment of the invention wherein DMR i5 utilized. The incident 10 light source is positioned a'c an angle of 45 relative to the paint f ilm. Three detectors are positioned in order to take optical property measurements at three different angles (as measured f rom the specular angle):
15 (1~ Detector No. 1 - 15 (near spec~lar);
(2) Detector No. 2 - 45 (perpendicular to the paint f ilm surface); and (3) Detector No. 3 - 110D (far from specular).
While the same angles may not be chosen for 20 a syste}n utilizing IMR or. O~, suitable angles ccsuld be easily determined by one skilled in the art.
The improved method of this invention can be used to characterize not only metallic pain~ films but any surface containing metallic particles, such 25 as plastics containing reflective metallic flakes.
The improved method is part~cularly usef ul in shading paint wherein the L*, ~ and b* values are determined for a standard. ~hen a batch of pain~ is manuactured according to a given formula; a painted panel of the batch is made and the L*, a~ and b~
values are determined. Often the batch of paint, even if carefully made, does not match the standard because of variations in pigments and color drift of pigment dispersions. The ~L*, ~a* and ~b* values of the batch are calculated and if outside ~f an lZZlB53 :L2 acceptable l:olerance value, calculatlons are made for the addi~ion of pigments in the form of mill bases and the mill bases added to ~che batch and a second panel prepared and values are measured as above. The 5 process is repeated until there is ~n acce~table color match ~etween the standard and the batch of pai nt .

Claims (3)

The embodiments of the invention in which an exclusive property or privilege is claimed are defined as follows:

1. An improved method for instrumentally characterizing the optical properties of a paint film containing metallic flakes by using multiangular spectrophotometric measurements to derive color constants for the paint, wherein the improvement comprises using three multiangular measurements utilizing the techniques of Detector Modulated Reflectance, taken at angles of about 15°, 45°, and 110°, as measured from the specular angle with an illumination angle of 45° relative to the metallic paint film being optically characterized and determining X, Y and Z tristimulus values of a paint film by using the following equations:

wherein R is the reflectance factor data, ?, ?, ? data on the sensitivity of the human eye, E is the irradiance of a light source and .lambda. function of wavelength in the visible light spectrum from 360-830 nanometers.

2. The improved method of Claim 1 in which perceptual color values of a paint film of lightness (L*), redness/greenness (a*), yellowness/blueness (b*), saturation (C) and hue (H) are determined using the following equations:

L*=116(Y/Yo)1/3-16 a*=500[(X/Xo)1/3-(Y/Yo)1/3]

b*=200[(Y/Yo)1/3-(Z/Zo)1/3]

C=(a*2+b*2)1/2 H=tan-1(b*/a*) where Xo, Yo and Zo are tristimulus values of a perfect white for a given illuminant; X, Y and Z are tristimulus values of color.

3. An improved method for instrumentally characterizing the optical properties of a metallic paint film, as recited in Claim 2 wherein said method is one step in a method for shading metallic paints.