Visual Determination of Hue Suprathreshold Color-Difference Tolerances Using CRT-Generated Stimuli

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1 Visual Determination of Hue Suprathreshold Color-Difference Tolerances Using CRT-Generated Stimuli Ethan D. Montag,* Roy S. Berns Munsell Color Science Laboratory, Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, 54 Lomb Memorial Drive, Rochester, New York Received 10 April 1998; accepted 31 July 1998 Abstract: Suprathreshold hue color-difference tolerances were measured at four color centers using CRT-generated stimuli. The tolerances, defined using CIELAB, were measured using two different methods of presentation. In the Absolute Experiment, the stimuli were presented at luminance levels that matched those of the previous object-color experiments, so that the CRT stimuli were nearly metameric to the originals. In the Relative Experiment, the white point of the monitor was defined as L* 100 at a corresponding chromaticity to the object-color viewing environment, but at a lower luminance level. The results from these two experiments followed the same general trends; however, they were significantly different from each other for three of the four color centers. The same trends were seen in the objectcolor results, although neither CRT experimental condition produced tolerances that were conclusively more similar to the object-color results than the other. The feasibility of the use of the CRT has been demonstrated. It is likely that parametric effects of stimulus presentation are the cause of the differences in results among the different experiments, as opposed to differences in the mode of appearance. These parametric effects can be studied more quickly and economically using a computer-controlled CRT display John Wiley & Sons, Inc. Col Res Appl, 24, , 1999 Key words: color differences; color tolerances; CRT display; parametric effects * Correspondence to: Ethan D. Montag Contract grant sponsor: Munsell Color Science Laboratory Industrial Color Difference Consortium 1999 John Wiley & Sons, Inc. INTRODUCTION During the last decade, the Munsell Color Science Laboratory has been engaged in research involving the development of a color-tolerance dataset for use in the testing and development of color-difference equations. 1 7 In 1995, the Munsell Color Science Laboratory established the Industrial Color Difference Evaluation Consortium. The purpose of the research program is to improve the effectiveness of automated industrial color-difference evaluation. 7 The RIT DuPont dataset, 5 the combined dataset developed from three experiments, 2 4 was based on experiments using color-difference pairs that were an automotive lacquer coating sprayed onto primed aluminum panels. In addition to the many hours needed in producing the raw samples, a great deal of time and labor was needed to prepare the samples for experimentation. A total of 959 sample pairs were produced in this manner for the three experiments, in which nineteen color centers were gauged. Because of the amount of labor and time necessary to produce these sample pairs, measuring color tolerances throughout color space is prohibitive when using this type of stimulus. Strocka, Brockes, and Paffhaussen 8 point out that at least 150 color centers ought to be investigated as a thorough basis for an empirical color-difference formula. A fourth experiment at the Munsell Color Science Laboratory 6,7 measured hue color-difference tolerances at 39 The use of the term color tolerance in connection with the experiments carried out in this and related work is based on historical precedent. The definition of tolerance is the allowable deviation from a standard and, therefore, is a misnomer in this context, unless the anchor pair is assumed to define the tolerance threshold. In actuality, these experiments are scaling color differences by comparing test differences against a standard difference. However, the results from these scaling experiments are useful in refining color difference formulae. 164 CCC /99/ COLOR research and application

2 color centers utilized a Fujix Pictrography 3000 digital printer 9 to produce sample pairs, in order to produce samples in-house and speed up the preparation time for the color-tolerance experiments. Due to limitations in the accuracy of the multidimensional color lookup table, limitations in digital precision due to quantization, nonuniform sampling of the color gamut within CIELAB, and print-to-print variability, the desired colorimetric coordinates of the samples were seldom achieved. This necessitated the production of multiple prints with slightly different digital count values in order to produce samples scattered mainly along the hue direction. After cutting the samples to size and measuring each sample, the samples were then sorted to make sample pairs that varied predominantly in hue with only slight differences in lightness and chroma. Despite this sorting technique, a more complicated statistical method, logit analysis with 3-dimensional normit function, was required to factor out the color differences in lightness and chroma from the total color difference. For this experiment, 393 color difference pairs were produced. From the above considerations, it was apparent to the Consortium that a new efficient method was needed to reduce the time, labor, and cost needed to produce objectcolor samples for use in color-tolerance experiments. As a first step towards this goal, the experiments described in this article were carried out to test the efficacy of using a computer-controlled cathode ray tube (CRT) to determine hue suprathreshold color-difference tolerances. These experiments were carried out in conjunction with the redetermination of hue tolerances of four color centers used by Qiao 6, and these results are reported in Qiao et al. 7 These data are also included here for comparison. In addition to the increased efficiency a CRT would provide for the study of color tolerances, the flexibility of the display would make possible the study of additional parametric effects on judgments of color tolerances. Factors such as surround and background luminance, sample size, sample separation (e.g., a gap between sample pairs), and sample luminance can be quickly manipulated on a CRT display. It may also be possible to simulate the surface appearance of the samples on a display to measure how surface factors such as texture and gloss influence color tolerance. As described in Qiao et al., 7 hue tolerances for four color centers, at L* 40 and C* ab 35, with h ab 30, 210, 240, and 300 were reevaluated to test the accuracy and reproducibility of the results of the original experiment. The tolerance values for the color centers located at h ab 30, 210, and 240 had large fiducial limits, and it was hoped that replicating these centers might reduce the uncertainty. The color center at with h ab 300 was also retested to reduce ambiguity in the location of the minimum in the curve relating perceived hue-tolerance to CIELAB hue angle. These same four color centers were reevaluated using the original samples (Fujix Pictrography) and new samples prepared by DuPont Automotive using sprayed aluminum panels colored with an acrylic-lacquer sprayed coating similar to the RIT DuPont samples. To test the efficacy of the CRT, the same four color centers were used as targets for producing sample pairs displayed on the CRT. The testing of these four color centers on the CRT was done in two ways. In one experiment, the luminance level of the samples on the CRT was matched to those used in the light booth in the original experiment to get as close a colorimetric (although metameric) match to the conditions of the original experiment. Therefore, the light from the samples and background ought to nominally stimulate the observers receptors identically to the samples and background in the original experiment. This type of color reproduction is described by Hunt 10 as exact color reproduction. This experiment will be referred to as the Absolute Experiment. In the second experiment, the D65 white point of the monitor was defined as L* 100 and the CIELAB values of the stimuli were reproduced on the monitor relative to this white point. This corresponds to Hunt s criterion of corresponding color reproduction to the extent that CIELAB color space can function as an appearance space. 11 This experiment will be referred to as the Relative Experiment. To the extent that the normalization of lightness in CIELAB can scale color differences in relation to the absolute level of illumination, the results of these two experiments should agree. Typically, the CIE Observer is used for color tolerance measurements, 12 and this is how the measurements on object-color samples have been carried out in this laboratory. Because the purpose of this research was to test the feasibility of the use of a CRT to evaluate color tolerances, the CIE observer was used to take advantage of existing instrumentation that facilitates efficient data collection. Therefore, direct comparisons of the tolerances between the CRT measurements made here and object-color samples are not strictly valid. However, these data do allow us to verify whether using the CRT is reasonable. The purpose of the following experiments is, therefore, to demonstrate that the use of the CRT can supersede objectcolor experiments, as reported by others In addition, by measuring hue color-difference tolerances under two different viewing conditions, we demonstrate how parametric effects can influence the results of this type of experiment. This is accomplished by comparing the current results from the CRT-generated stimuli to the results from color tolerance measurements determined using object-color stimuli. 7 EXPERIMENTAL To use a computer-controlled CRT for visual experiments, a method is needed to convert the desired colorimetric values to digital counts for accurate color display. This colorimetric characterization can be achieved either through the use of a multidimensional color lookup table based on a large number of measurements, or through the use of an analytic model that describes the relationship between digital counts and the CIE tristimulus values resulting from phosphor emission. References describe such a model and a method for characterizing a CRT. The first stage of the model is a nonlinear transform based on measuring the monitor s characteristic system gain, offset, and Volume 24, Number 3, June

3 gamma for each channel. This converts digital counts to radiometric scalars, RGB. A second linear transformation converts the scalar RGB values to CIE tristimulus values. In addition, an additive term is included, which describes the contribution from ambient flare reflecting off the CRT s faceplate or as a result of measurable interreflections from neighboring pixels. This model, referred to here as the GOG model (for Gain, Offset, and Gamma), was implemented and its precision and accuracy were tested for producing the desired colors for use in the experiment. Monitor Setup A Sony Trinitron Multiscan 15sf monitor, modified by Sony to increase its peak luminance, was used in these experiments to achieve higher absolute light levels for the experiments. The monitor was controlled by a Macintosh PowerPC in 24-bit color mode. Before calibration, the gamma of the monitor was visually adjusted, using a desk accessory (Knoll Gamma), to have a value close to 1.0 to ensure that the color lookup tables followed a smooth function. The monitor was calibrated and characterized using the GOG-model, and measurement of the colors used in the experiment were taken using an LMT C-1200 colorimeter. Based on these measurements, the monitor was set up for the Absolute and Relative Experiments as described in the following sections. Absolute Experiment Based on the values of the illuminance and chromaticity of the Macbeth Spectralite light booth used in the original experiment (CCT 6550K), the CIE observer FIG. 1. The color gamut of the CRT in CIELAB space for the Absolute viewing condition. The values are calculated with a white point (L* 100, a* 0, b* 0) set at x and y with a luminance of cd/m 2 (CIE observer). (Colors shown are approximate.) 166 COLOR research and application

4 TABLE I. CIELAB coordinates of the color centers used in the experiment. The target values used in producing the displayed colors and the actual values calculated from the mean of values of the measured colors used in the experiment are shown. Original Target values for Absolute Experiment Actual values for Absolute Experiment Target values for Relative Experiment Actual values for Relative Experiment Color center 1 L* C* ab h ab Color center 2 L* C* ab h ab Color center 3 L* C* ab h ab Color center 4 L* C* ab h ab chromaticity of a perfectly diffusing reflector was x and y with a luminance of cd/m 2, measured using a PhotoResearch PR680 spectroradiometer. This white point, represented now in CIE due to the subsequent use of a LMT C-1200 for monitor calibration, was defined as L* 100, a* 0, and b* 0 for the determination of the CIELAB values for the colors produced on the monitor in the Absolute Experiment. That is, the same numerical chromaticity values were used as the white point based on the CIE observer and the tristimulus value Y was set equal to the luminance. Because the light-booth white point is much more luminous than the white point attainable on the monitor, the range of lightness attainable in CIELAB L* units was reduced. The maximum L* producible on the monitor, was approximately 57 in this mode. The gamut of the monitor in CIELAB space based on the light-booth white point is shown in Fig. 1. The CRT gamut was limited in chroma as compared to that of the object-color samples produced by automotive paints and the Fujix Pictrography 3000 digital printer for two of the four color centers: color centers 2 and 3. As a result, the chroma values of the color centers originally tested were not all attainable. Table I shows the target CIELAB values (from Refs. 6 and 7) and the actual values of the color centers tested in this experiment. Note that the limitations were for chroma in color centers 2 and 3 (L* 39.6, h and L* 38.7, h 239, respectively). Relative Experiment The most luminous color producible on the monitor with the same chromaticity as the light-booth white point, (x , y (CIE observer), Y cd/m 2, measured off of a pressed Halon tablet in the light booth) was defined as L* 100, a* 0, b* 0 for the Relative Experiment. The colors used in the experiment were calculated in CIELAB relative to this white point. This is the way that CIELAB is typically implemented. Figure 2 shows the gamut of the monitor in CIELAB space for the Relative Experiment. Because of the gamut limitations, the target color centers used in this experiment were not attainable. Table I shows the CIELAB values of the color centers used in this experiment. Again, color centers 2 and 3 (L* 39.6, h 210.6, L* 38.7, h 239, respectively) were out of gamut. It should be noted that CIELAB values in Table I are calculated differently based on the differences in white point used in the two experiments and the use of the CIE Observer for the CRT experiments. The CIELAB gamut of the monitor was larger in this experiment than that produced in the Absolute Experiment. However, the resolution of the space was coarser because of the greater quantization in digital count RGB. That is, a change of one digital RGB value in the Absolute Experiment, exhibits a smaller E* ab than the identical change in the Relative Experiment. In a typical computer monitor with 8-bit resolution per channel, the resolution in an experiment where the white point is normalized to L* 100 can be very close to a one-unit change in E* ab. 19 This can severely limit the ability to use the CRT for color tolerance research. However, 10-bit or better resolution is increasingly available with the introduction of graphic video boards for personal computers. Viewing Conditions The experiments were conducted using a specially constructed booth on which a Macbeth Spectralight SPL-65 Luminaire was mounted. Therefore, the illumination for the booth was the same as that used in the object-color experiments of Qiao et al. 6,7 The walls of the light booth were lined with black velvet, and the bottom of the booth was covered with a 20% luminance factor gray matte cardboard surface. The back wall of the light booth could be opened up to allow a CRT placed behind the booth to be viewed through the booth. It should be noted that when CIELAB values are reported for the two different experiments, they are based on calculations done with different white points. Absolute Experiment Volume 24, Number 3, June

5 FIG. 2. The color gamut of the CRT in CIELAB space for the Relative viewing condition. The values are calculated with a white point (L* 100, a* 0, b* 0) set at x and y with a luminance of cd/m 2 (CIE observer). (Colors shown are approximate.) A black baffle was mounted through the booth to allow the viewing of the CRT without light from the booth reflecting off the screen (see Fig. 3). The baffle was 30 in long with an opening large enough to view the entire monitor screen. The monitor was placed up against the far end of the baffle, and the observer viewed the monitor through the baffle at a distance of approximately 36 in. The light booth was illuminated using the daylight simulator (D65) with a CCT of 6550K with an illuminance of 1840 lux, measured with a Minolta Chroma Meter II, with the black velvet lining and gray bottom cardboard surface in place. The stimulus configuration for the Absolute Experiment is shown in Fig. 4(a). The display subtended a visual angle of The samples subtended a visual angle of The anchor pair was displayed on the left. The CIELAB coordinates of this pair are shown in Table II. The in E* ab value of the anchor pair was The test pairs were presented on the right. A one-pixel black line (0.02 ) surrounded each of the anchor pair and test pair colors with a one-pixel black line between the members of each pair. The stimuli were presented in a darkened room. The monitor background was set to L* 49.1, a* 0.33, b* Relative Experiment The configuration for the Relative Experiment was the same as above except that the surrounding 0.4 wide border of the monitor display was set to the reference white of the experiment (x , y , Y cd/m 2 ). The CIELAB coordinates of the anchor pair are shown in Table II. The E* ab of the anchor pair was The illumination from the light booth was turned off, and the stimuli 168 COLOR research and application

6 FIG. 3. Configuration of light booth, monitor, and baffle. were viewed with the room lights off. The monitor background was set to L* 50.1, a* 0.43, b* The stimulus configuration for the Relative Experiment is shown in Fig. 4(b). These procedures were repeated a week later to see how the monitor s stability and the measurement accuracy would affect the values of the samples chosen. Although there was a change in the CIELAB values between the two sets of measurements, the change was characterized by a shift of all the values by approximately the same amount, as shown in Fig. 5, for the Relative Experiment. Color center 4 (h* 300 ) showed the largest dispersion of values over time and a decrease in percent variance explained by the first eigenvector of only 0.24% for the Absolute Experiment values. A number of possible factors could cause a change in the measured values of the samples at different times: (1) an instability in the monitor, which causes a drift over time (although a consistent drift was not detected throughout a series of measurements made over time); (2) a lack of precision in the colorimeter; or (3) a lack of precision in the repeatability of measurements due to differences in the exact positioning of the colorimeter head in front of the monitor. The first factor is most likely, because the LMT C-1200 colorimeter (which was positioned within a subscribed area on the monitor screen) averages over a large Stimulus Selection The GOG model was used to determine the digital counts of the test samples in the experiment. This model was implemented with an additive term that takes into account the interreflection flare contributed by the backgrounds used in each experimental condition. The RGB values were determined with floating-point precision in a range around each color center varying only in CIELAB hue by 3or4 (depending on the color center) in steps of 0.1. These RGB values were then quantized in 8-bits, and the CIELAB values for these quantized RGB values were calculated using the GOG model. Due to quantization, the 60 to 80 target values would be reduced to about 14 to 35 values for the Absolute Experiment and about 8 to 14 values for the Relative Experiment, due to the greater effect of quantization in this gamut. These RGB values were then used to display colored patches on the monitor, which were measured with an LMT C-1200 colorimeter. The patches were displayed using the same colored background used in each experimental condition. The tristimulus values of the test patches were measured (the average of three measurements per patch without replacement) and were converted to CIELAB coordinates. An eigenvector analysis was performed on the sample coordinates to determine the percent variance explained by the first eigenvector. This value is a measure of linearity indicating that the samples vary along one dimension. Table III shows the percent variance explained by the first eigenvector for each color center in each experimental condition. Notice that the Absolute Experiment has values closer to 100% due to the greater resolution available in this gamut representation. FIG. 4. The stimulus arrangement on the CRT: (a) the absolute condition; (b) the relative condition. Volume 24, Number 3, June

7 TABLE II. CIELAB coordinates and color differences of the anchor pairs used in the two experiments. Absolute Condition Anchor Pair Top Bottom L* a* b* H* ab 0.99, C* ab 0.07, L* 0.25, E* ab 1.02 Relative Condition Anchor Pair Top Bottom L* a* b* H* ab 0.86, C* ab 0.38, L* 0.21, E* ab 0.97 area with an integrating head that is larger than the area of its detector, and our previous experience with this instrument has shown it to be quite precise. Based on further analysis of the measured values, it was concluded that, although there were changes in the colorimetric values of the samples over time, the color differences measured in CIELAB units between samples were stable. Figure 6 shows for the Relative Experiment a comparison of H* ab values calculated for all possible pairs using the data from the first measurement set compared to the H* ab values calculated for all possible pairs using the second measurement set. The solid line shows a line of unity slope. If the points fell along this line, it would indicate no change in the pair-wise H* ab values between the two successive measurement sets. The data do fall close to this line. For Color Center 1, the points fall slightly below the line of unity slope, meaning that the hue differences were slightly larger for measurement 1 than measurement 2. Despite any change over time, the stability of the color differences between samples over time allows for the use of the CRT, because the goal of this type of research is to measure color tolerance around arbitrary color centers. Berns 13 reached a similar conclusion in a previous study evaluating the feasibility of using a computer-controlled CRT for color-tolerance research. TABLE III. Eigenvector analysis showing the percentage of variance explained by the first eigenvector for all colors measured and those used in the experiment. Percent of variance explained by the first eigenvector Absolute Experiment Relative Experiment All samples Samples used All samples Samples used Color center Color center Color center Color center FIG. 5. Shift in the measured CIELAB coordinates over a period of one week. The circles are the first measurements, the Xs are the second measurements one week later. Data from the Relative Experiment: (a) Color Center 1; (b) Color Center 4. For each color center and experimental condition, a table of H* ab, L*, and C* ab values for every pair of samples was constructed. From this table, sample pairs were chosen so that the H* ab values were distributed over the range encompassing the threshold values predicted from the original object-color experiments. The samples were chosen so that L* and C* ab values were small, keeping most of the variation in hue. A pilot experiment was performed on 5 subjects to ensure that the 50% tolerance level was approximately centered within the range of samples chosen, and that the sampling was appropriately distributed. The final 170 COLOR research and application

8 choice of sample pairs was adjusted based on these pilot data. The average of the CIELAB values for the samples chosen were used to calculate the actual color centers presented in Table I. The percent variance explained by the first eigenvector for the samples used in the experiment are shown in Table III. The percent variance ranged from %. In comparison, the percent variance explained by the first eigenvector for the stimuli used by Qiao et al., 6,7 produced on the Fujix Pictrography printer, ranged from %, indicating undesired variation in chroma and lightness. The painted samples used for the supplemental experiments to Qiao et al. 7 had a comparable degree of variance to the CRT stimuli used here. The percent variance for these painted samples ranged from %. 7 Procedure Thirty color-normal subjects, ranging from 22 to 51 years of age took part in the experiment. The subjects were faculty, staff, and students of the Center for Imaging Science with a wide range of experience in making tolerance judgments. These experiments were run in conjunction with the supplemental experiment described in Qiao et al. 7 After completing a series of 80 trials using object-color samples, the booth was configured for the Absolute Experiment [light booth on, no reference white border, see Fig. 4(a)]. The Absolute Experiment consisted of 42 trials in which sample pairs for all four color centers were intermixed and presented in a unique random order for each subject. Subjects adapted to the display conditions for two minutes 20 before beginning the trials. After completing the Absolute Experiment, the light booth illuminant was turned off and the Relative Experiment [light booth off, reference white border, see Fig. 4(b)] was begun. Subjects again adapted for two minutes before starting. The Relative Experiment consisted of 34 trials, in which sample pairs for all four color centers were intermixed and presented in a random order that was different for each subject. In each experiment, an anchor pair was presented on the left and did not vary throughout the experiment. A test pair was presented on the right, and the subjects task was to indicate with a key press whether the color difference in the test pair was greater or less than the color difference in the anchor pair. Subjects could take as much time as they wanted to make their judgments, which typically took only a few seconds per trial. Stimulus presentation and the recording of the responses were under computer control. This is in contrast to the manual sorting and scoring of objectcolor samples in previous experiments. Both experiments were completed within min. RESULTS AND DISCUSSION The data were analyzed using probit analysis, 21 a univariate statistical method that locates a median threshold from binary choice (in this case, greater or less-than) visual data. FIG. 6. Comparison of the H* ab values for all possible pairs of colors between the measurements taken on two occasions one week apart. Data from the Relative Experiment: (a) Color center 1 (30 ); (b) Color Center 4 (300 ). An overall fit of the data is assessed by a chi-square test, and a heterogeneity factor is applied if the probability of chisquare was less than 0.1. In no case was a heterogeneity factor needed, indicating that the probit model was adequately fit to the data. The T50 (50% tolerance level) and the fiducial limits are calculated for each color center. Because of the possibility that the sample variation in chroma and lightness (albeit small) might affect the results, the data were also analyzed using a multidimensional sta- Volume 24, Number 3, June

9 FIG. 7. T50 values and fiducial limits for the four color centers in the Absolute and Relative Experiments. the results from the probit analysis indicated a better fit to the model and were used in the analysis. The fiducial limits were on average 11.6% of the measured tolerance, with a range of about 7 25% for the different color centers. In comparison, the results in Qiao et al. 7 for the corresponding color centers show a much wider range of uncertainty (see their Fig. 5). For the corresponding color centers, these fiducial limits ranged from 13% to over 100%, depending on the color center. The supplemental data 7 from the samples produced by DuPont Automotive for the same color centers showed a fiducial range of 6 81% with a mean of 23.8%. These samples had much less lightness and chroma variation than the Pictrography samples and are comparable to the CRT samples in this regard (see Table III above and Table IV of Qiao et al. 7 ). Fiducial limits of 20% are not uncommon in experiments using objectcolor samples. 23 Based on these data, the results from the CRT experiments demonstrate smaller uncertainties in the tistical analysis, the SAS logit program with 3-D normit function. 6,7,22 This technique fits the transformed Z-scores of the data in a three-dimensional space. A score statistic is incorporated in the analysis to determine whether interactions among dimensions are indicated. This statistic was not significant for all analyses. An additional program is used in which the coefficients of the terms related to hue and chroma differences are set to zero, and the T50 and the fiducial limits are calculated. A heterogeneity factor is applied if the chi-square value from the normit model is large. The results for the probit analysis are shown in Fig. 7. The results for both analyses (probit vs. 3-D logit with normit) were identical except for color center 3. In both the Absolute and Relative Experiments, the values of the T50 and fiducial limits were different using the two different types of analysis. For the Absolute Experiment, the T50 for color center 3 was 2.60 with a fiducial range from using the multidimensional analysis. This T50 was slightly lower than that of the probit analysis with a fiducial range that extended to lower values. For the Relative Experiment, the T50 was 1.70 with a fiducial range from using the multidimensional analysis. Again, this T50 was lower than that from the probit analysis, but the fiducial range was wider. A heterogeneity factor was applied in this case, which increased the fiducial range. The differences in results between the two analyses for color center 3 is likely due to the selection of samples used for these color centers. The 50% tolerance levels were not centered near to the middle of the range of test pairs used for these color centers. Therefore, the estimates of these values were based on psychometric functions that were computed from the existing data, which incompletely sampled the range of the psychometric function. This is shown in Fig. 8. The difference in results was not due to the influence of chroma and lightness in the judgments, because inspection of the sample pairs used shows that the ratio H* ab to E* ab was never less than Because of this, and the fact that the T50s from the logit are within the probit fiducial limits, FIG. 8. Results of the probit analysis for color center 3 (240 ) for: (a) the Absolute Experiment; (b) the Relative Experiment. The psychometric function fit by the probit analysis is shown as the solid line. The upper and lower fiducial limits are marked by the dotted curves. The location of the T50 values are shown by the dot-dash lines drawn to the axes. 172 COLOR research and application

10 TABLE IV. T50 tolerances, fiducial limits, and anchor pair color difference for the Absolute Experiment presented for the CIE 1964 Standard Observer. CC1 CC2 CC3 CC4 CIE 1964 Standard Observer Calculations Absolute Experiment E* ab Anchor Pair 0.90 Color center Lower coords H* ab fiducial limit L* 36.7 C* ab 31.7 h ab 33.9 L* 40.3 C* ab 24.6 h ab L* 39.7 C* ab 27.1 h ab L* 37.9 C* ab 33.9 h ab Upper fiducial limit determination of tolerances than those of object-color experiments. These reduced uncertainties are likely a result of the experimental procedure involved in judging the stimuli as opposed to variation in the stimuli themselves. As indicated above, object-color samples such as the set manufactured by DuPont Automotive have the same degree of chroma and lightness intrusion, yet show greater uncertainty in results. 7 The CRT experiments afford greater control of experimental conditions such as sample positioning, viewing distance, and sample illumination. In the object-color experiments, subjects typically manipulate the samples, changing their appearance in order to get a better view. For the CRT experiments, the presentation is constant. The spectral power distribution of each of the primaries of the CRT was measured at each channel s peak output. Each of these spectral power distributions was then scaled so that, when the CIE Observer tristimulus values were calculated, the luminance would be equal to that measured during the calibration of the monitor. Based on these scaled spectra, a tristimulus matrix, which is used to convert digital RGB values to tristimulus values, was calculated using the CIE Observer Color-Matching Functions. The CIE tristimulus values of the internal reflectance flare was modeled as a linear combination of the three phosphors. Based on these RGB values, the CIE tristimulus values, corresponding to the internal flare, were calculated. Using the new tristimulus matrix and internal flare values calculated for the 10 observer, it was now possible to convert the tolerance values into those for the 10 Observer by using the RGB values for the monitor as a conversion space. That is, the CIELAB tolerance values determined in the experiment based on the 2 observer were converted into monitor RGB values. Then the RGB values were converted into CIELAB values based on the 10 observer. Identical white points calculated for each CIE Observer were used so that they had a value of L* 100, a* 0, and b* 0 in the calculations of CIELAB values for both the 2 and 10 observer. The CIELAB coordinates corresponding to the color centers, tolerance thresholds, and the upper and lower fiducial limits were calculated for each color center. These were calculated for both increasing and decreasing hue angle, so that there were seven sets of CIELAB coordinates produced for each color center. The monitor RGB values for each of these were calculated, and then they were converted into CIELAB coordinates for the 10 Observer. The CIELAB color differences for the tolerances and fiducial limits were calculated from the color centers, and then these were averaged to produce the tolerance levels and fiducial limits for each color center for the 10 Observer. The anchor pair samples were also converted to the 10 Observer and the E* ab was calculated. These values are shown in Tables IV and V. These new tolerance values and fiducial limits are reported here as E* ab values, although the contribution from chroma and lightness is negligible so that they can be considered as hue tolerances. These tolerances and fiducial limits, as well as the color difference of the anchor pairs, are corrected for chroma by calculating the E* 94 using the following equation: 24 E* 94 L* C * ab (1) S L 1 2 k L S L 2 k C S C S C C* ab,standard S H C* ab,standard H * 2 1/ 2 ab k H S H k L k C k H 1 for the reference conditions. C* ab, Standard was set to the chroma of each color center for the tolerance calculations and was the geometric mean of TABLE V. T50 tolerances, fiducial limits, and anchor pair color difference for the Relative Experiment presented for the CIE 1964 Standard Observer. CC1 CC2 CC3 CC4 CIE 1964 Standard Observer Calculations Relative Experiment E* ab Anchor Pair 0.93 Color center Lower coords H* ab fiducial limit L* 38.0 C* ab 27.6 h ab 27.0 L* 40.5 C* ab 23.4 h ab L* 40.2 C* ab 26.1 h ab L* 39.0 C* ab 31.9 h ab Upper fiducial limit Volume 24, Number 3, June

11 TABLE VI. T50 tolerances, fiducial limits, and anchor pair color difference for the Absolute Experiment presented for the CIE 1964 Standard Observer using E* 94. E* 94 tolerances based on CIE 1964 standard observer Absolute Experiment E* 94 Anchor Pair 0.88 E* 94 tolerance threshold Lower fiducial limit Upper fiducial limit CC CC CC CC the chroma values for the two colors in each anchor pair for the anchor pair calculations. These values are presented in Tables VI and VII. These new tolerance values are normalized by dividing by the E* 94 of the anchor pair used in each experimental condition. The resulting tolerances and fiducial limits are presented in Fig. 9, along with the results from Qiao et al. 7 (their Table VI and Fig. 9) for the corresponding color centers. The data from Qiao et al. have been adjusted for chroma using CIE94 and are based on the uncertaintyweighted average of the pooled data. 7 As with the T50 values shown in Fig. 7, the tolerances are significantly different from each other for all but color center 4 (nominally 300 ). For the other three color centers, the Absolute Experiment produced greater tolerance values than the Relative Experiment, although the same trend is noticeable in the data, that is, an increase in the tolerance threshold from the color center at and again to 240 with a lower value again at 300. This same trend is present in the pooled data from Qiao et al. 7 From these data it is unclear whether the Absolute or the Relative Experiment produced results that are more like those of the objectcolor experiments. Color Centers one and four (30 and 300 ) used stimuli with CIELAB values very close to those of the supplemental experiments in Qiao et al. 7 Color Centers two and three (210 and 240 ) used samples of lower chroma due to gamut limitations. Although the Relative TABLE VII. T50 tolerances, fiducial limits, and anchor pair color difference for the Relative Experiment presented for the CIE 1964 Standard Observer using E* 94. E* 94 tolerances based on CIE 1964 standard observer Relative Experiment E* 94 Anchor Pair 0.90 E* 94 tolerance threshold Lower fiducial limit Upper fiducial limit CC CC CC CC FIG. 9. T50 values and fiducial limits presented in the E* 94 units calculated for the CIE observer. These values are normalized by dividing by the anchor pair E* 94 color difference. Also shown are the pooled results from the supplemental data in Qiao et al. 6 Experiment results for these two color centers are a closer match to the pooled tolerances, it must be remembered that these data were scaled by C* ab in the E* 94 equation and normalized by the anchor pair difference. In addition, the sample sizes ( 5 7 in Qiao et al. vs. 3.6 here) and separations (abutted in Qiao et al. vs. black line here) were different. In general, all three experiments demonstrate similar trends in the results. Therefore, continued experimentation using the CRT, in either presentation mode, can facilitate the refinement of color tolerance measures by looking at the relative changes in tolerance values in different locations and directions in color space. There were two competing hypotheses for the possible outcomes of the experiments. The first hypothesis predicted that the results from the Absolute Experiment would more closely match the results from the object-color experiment, because the stimuli being used were metameric to those used in the object-color experiments. This corresponds to Hunt s exact color reproduction. 10 The alternative hypothesis was that, to the extent that CIELAB operates as a color appearance space 11 (although it is intended as a uniform color space), due to the chromatic adaptation terms and the subtractive terms corresponding to opponent-colors, the performance of the Relative Experiment should be more like the object-color results. This corresponds to Hunt s corresponding color reproduction. 10 Clearly, the data presented here do not resolve the issue. Because of limitations in producing an exact reproduction of the light-booth environment, including background and surround adaptation levels, and limitation of the use of CIELAB as a color-appearance space, neither hypothesis is likely to be entirely correct. This is a problem not only in the laboratory, but also in practice, where color tolerances are used in industry. The same issues involved in moving from a light booth to a CRT exist when applying laboratory results to real world situations. That is, how well do the results from the laboratory apply when parameters such as illumination, adaptation, sample size, sample spacing, etc. vary? Continued research on such parametric effects will be 174 COLOR research and application

12 conducted in this laboratory under the auspices of the Munsell Industrial Color Difference Evaluation Consortium. Phenomenologically, the samples in the Relative Experiment had an appearance much closer to the corresponding object-color samples. The samples in the Absolute Experiment appeared brighter and more colorful than the objectcolor samples. The background in the Absolute Experiment was not perceived as a middle gray, despite the light booth being illuminated around the baffle. It is possible that the noncontiguity introduced by the baffle diminished the influence of the surrounding light booth on the appearance of the display. 25 Subjects had more difficulty making greater-than/lessthan judgments in the Relative Experiment. This was likely a result of the coarser representation of color space in this experiment. The same relative color differences in CIELAB were produced by smaller changes in the RGB digital counts. It is interesting that the difference in defining the representation of CIELAB space in the two experiments was manifested in this phenomenological difference in the perceived difficulty of the judgments, but was not clearly evident in the results. Without the use of anchor pairs (acceptability as opposed to perceptibility judgments), it is likely that the tolerance thresholds would have been greater for the Relative Experiment than the Absolute Experiment. The opposite effect was seen for color centers one, two, and three. Comparisons to Other Studies Berns 13 compared CRT-generated stimuli with acryliclacquer coated paint samples in a color-tolerance feasibility study of one color center. In this experiment, the illumination of the light booth was reduced so that the samples generated on the CRT and the paint samples viewed in the light booth would have the same luminance. The CRT was placed behind the light booth and viewed through an opening cut in the back of the booth. The CRT-generated stimuli were judged with the light booth on (light surround) and with the light booth off (dark surround). A white strip was displayed on the CRT in order to have the CRT stimuli appear as related colors and to define the white point for the image. The CRT viewing conditions in this experiment were similar to the Absolute Experiment presented here, because the CRT colors were metameric to the painted samples. However the luminance levels were lower in Berns experiment. Berns found that intra-observer uncertainty was greater at these lower light levels than for object-colors tested at higher light levels, as indicated by larger values of the chi-square statistic. 4,5 In addition, judgments made on the CRT-generated stimuli had the greatest variability. To the contrary, the present study shows that, at the higher light levels used here, uncertainty is reduced with the CRT. This is likely due to the consistency in sample presentation with the CRT. Berns 13 found that there was a statistically significant difference between the two CRT conditions (light surround vs. dark surround), but that neither of these were significantly different from the surface color samples. Berns concluded that the results confirmed the feasibility of using CRT-generated stimuli for color-tolerance measurements, and that the reduced luminance of the CRT did not influence the tolerance estimates. The present results show that the use of the CRT can reduce tolerance uncertainty (inter-observer uncertainty) and decrease intra-observer uncertainty as indicated by the smaller chi-square values. Differences in parametric factors such as absolute luminance level, surround luminance factor, sample size and separation, etc., may be factors in the differences between these studies. There may also be greater stability in present day computer monitors. Both the Berns study 13 and the current work agree in the conclusion that it is feasible to use CRT-generated stimuli for measuring color tolerance. Rich et al. 14 had subjects compare color differences simulated on a CRT with object-color pairs viewed in a light booth. In their experiment, the luminance of the light booth was lowered to match that of the CRT. The colors on the CRT were not measured directly, but were produced by the analytic model used to characterize the CRT based on calibration measurements. In addition, the white points of the monitor and the light booth were different in order to ascertain how color differences on the CRT compared to color differences under different light-booth illumination. The authors concluded that the analytic model used to develop color simulation on a CRT was more accurate than the models used in typical object-color reproduction. Because this experiment involved aspects of cross-media viewing and adaptation, comparison of their results to the present results is difficult. Although the mode of appearance may affect the tolerance thresholds, the results of Indow et al. 15 would argue against this hypothesis. They found that although aperture and simulated surface colors had color appearances that were drastically different, discrimination ellipsoids were identical. In addition, Berns 13 found no statistical difference between CRT-generated stimuli and painted samples in their study. CONCLUSIONS The results from the present experiment demonstrate the feasibility of using CRT-generated stimuli for determining color tolerances. For the color centers measured, in which object-color samples produced tolerances with large uncertainties, the use of the CRT reduced the uncertainty. The results from these experiments indicate that the relative trends in the change in perceived hue tolerance with CIELAB hue angle are fairly consistent under differing viewing conditions. It is recommended that the use of an analytic model such as the GOG model plus the flare term used here be used only as a starting point for determining samples for display on the CRT. Measurements of the colors presented on the CRT screen and selection of samples based on these measure- Volume 24, Number 3, June

13 ments is required to achieve the requisite accuracy for color-tolerance measurement. It is likely that the differences between the two CRT experiments presented here and differences between these and other object-color experiments are due to differences in parametric effects. The effect of changes in sample size, luminance level, surround and background luminance factor, sample separation, etc., can be studied more quickly and economically using a CRT display. These results can then be related to the results of color tolerances measured under standard conditions defined for viewing surface colors. 12 We have begun such a research program under the auspices of the Munsell Color Science Laboratory Industrial Color Difference Consortium. Our capabilities have been expanded with the addition of 10-bit color, which will allow better resolution in the specification of colors to be displayed and in the determination of color tolerances. In addition to the parametric effects mentioned above, the CRT will provide us the opportunity to simulate the effects of other parametric factors such as texture and gloss in order to better specify color tolerances for use in different industrial applications. ACKNOWLEDGMENTS This research was supported by the Munsell Color Science Laboratory Industrial Color Difference Consortium. The current members are 3M, Datacolor International, Detroit Color Council, DuPont Automotive, Dystar, Bayer Corporation, Inter-Society Color Council, Macbeth, Society of Plastics Engineers, PPG, and Xerox Corporation. The authors wish to thank Lisa Reniff and Dave Wyble for their assistance in running the experiment, the observers who volunteered their time, and Tsuneo Kusunoki of the Sony Corporation for arranging the modification of a production display and its donation. Thanks also to Rolf G. Kuehni for critiquing the article manuscript. The authors also thank LMT Lichtmesstechnik GmbH, Berlin; Fuji Photo Film Co., Ltd.; Sony; and Macbeth for the donation of the equipment used in this research to the Munsell Color Science Laboratory and DuPont for the production of the samples used in this study. 1. Alman DH, Berns RS, Snyder GD, Larson WA. Performance testing of color-difference metrics using a color tolerance dataset. Color Res Appl 1989;14: Reniff LA. Visual determination of color differences using probit analysis: phase II. Rochester, New York: Rochester Institute of Technology; M. S. Thesis. 3. Snyder GD. Visual determination of industrial color-difference tolerances using probit analysis. Rochester, New York: Rochester Institute of Technology; M. S. Thesis. 4. Balonon-Rosen MR. Quantification of industrial-sized color differences: phase II-S. Rochester, New York: Rochester Institute of Technology; M. S. Thesis. 5. Berns RS, Alman DH, Reniff L, Snyder GD, Balonon-Rosen MR. Visual determination of suprathreshold color-difference tolerances using probit analysis. Color Res Appl 1991;16: Qiao Y. Visual determination of hue suprathreshold tolerances. Rochester, New York:Rochester Institute of Technology; M. S. Thesis. 7. Qiao Y, Berns RS, Reniff L, Montag E. Visual determination of hue suprathreshold color-difference tolerances. Color Res Appl 1998;23: Strocka D, Brockes A, Paffhausen W. Influence of experimental parameters on the evaluation of color-difference ellipsoids. Color Res Appl 1983;8: Suda Y, Ohbayashi K, Onodera K. A kinetic study of chromogenic photothermography. J Imag Sci Tech 1993;37: Hunt RWG. Objectives in colour reproduction. J Phot Sci 1970;18: Fairchild M. Color appearance models. Reading, MA: Addison Wesley; Robertson AR. Guidelines for coordinated research on color-difference evaluation. Color Res Appl 1978;3: Berns RS. Color tolerance feasibility study comparing CRT-generated stimuli with an acrylic-lacquer coating. Color Res Appl 1991;16: Rich DC, Alston DL, Allen LH. Psychophysical verification of the accuracy of color and color-difference simulation of surface samples on a CRT display. Color Res Appl 1992;17: Indow T, Robertson AR, von Grunau M, Fielder GH. Discrimination ellipsoids of aperture and simulated surface colors by matching and paired comparison. Color Res Appl 1992;17: Berns RS, Motta RJ, Gorzynski ME. CRT colorimetry. Part I: theory and practice. Color Res Appl 1993;18: Berns RS. Methods for characterizing CRT displays. Displays 1996; 16: Commission Internationale de l Eclairage (CIE). The relationship between digital and colorimetric data for computer-controlled CRT displays. Publication CIE# 122. Austria: Bureau Central de la CIE; Saunders B. CIELAB spacing of digitally specified colors on a 24-bit CRT monitor. J Imag Tech 1987;13: Fairchild MD, Reniff L. Time course of chromatic adaptation for color-appearance judgments. J Opt Soc Am A 1995;12: Finney DJ. Probit analysis, 3rd Ed. Cambridge: Cambridge Univ Press; SAS Institute Inc., SAS user s guide: statistics, latest version. Cary, NC: SAS Institute Inc. 23. Luo, MR, Rigg B. Chromaticity-discrimination ellipses for surface colors. Color Res Appl 1986;11: Commission Internationale de l Eclairage (CIE). Industrial colourdifference evaluation. Publication CIE# 116. Austria: Bureau Central de la CIE; Fairchild MD. Considering the surround in device-independent color imaging. Color Res Appl 1995;20: COLOR research and application

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