Uniform colour spaces based on the DIN99 colour‐difference formula

Cui, Guihua; Luo, M. Ronnier; Rigg, B.; Roesler, G.; Witt, Klaus

doi:10.1002/col.10066

Cited by 96 publications

(89 citation statements)

References 10 publications

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“…The optimal color stimuli for the normal observer were computed for the CIE standard illuminant D65 and expressed in the CIELAB [31] and DIN99d [32] color spaces. The corresponding color volumes for abnormal color vision were computed using models simulating for normal trichromatic observers the appearance for dichromats and anomalous trichromats.…”

Section: Macadam Limits or Rösch-macadam Limitsmentioning

confidence: 99%

“…The lightness planes computed were in the range 1-99 in unitary steps. The XYZ tristimulus values were computed using the CIE 1931 color-matching functions [31] linearly interpolated for 0.1 nm, and their representation in the CIELAB [31] and DIN99d [32] color spaces was also calculated. The CIELAB space was selected for comparison with previous estimates and DIN99d was selected because of its improved uniformity over CIELAB but still has attributes similar to those of the CIELAB formula [32,33].…”

Section: Color Normalmentioning

confidence: 99%

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Number of discernible colors for color-deficient observers estimated from the MacAdam limits

et al. 2010

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We estimated the number of colors perceived by color normal and color-deficient observers when looking at the theoretic limits of object-color stimuli. These limits, the optimal color stimuli, were computed for a color normal observer and CIE standard illuminant D65, and the resultant colors were expressed in the CIELAB and DIN99d color spaces. The corresponding color volumes for abnormal color vision were computed using models simulating for normal trichromatic observers the appearance for dichromats and anomalous trichomats. The number of colors perceived in each case was then computed from the color volumes enclosed by the optimal colors also known as MacAdam limits. It was estimated that dichromats perceive less than 1% of the colors perceived by normal trichromats and that anomalous trichromats perceive 50%-60% for anomalies in the medium-wavelength-sensitive and 60%-70% for anomalies in the long-wavelength-sensitive cones. Complementary estimates obtained similarly for the spectral locus of monochromatic stimuli suggest less impairment for color-deficient observers, a fact that is explained by the two-dimensional nature of the locus.

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Section: Macadam Limits or Rösch-macadam Limitsmentioning

confidence: 99%

Section: Color Normalmentioning

confidence: 99%

Number of discernible colors for color-deficient observers estimated from the MacAdam limits

et al. 2010

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“…A uniform color space, widely used in industry, is the CIE-L * a * b * , which allows one to visualize the color solid in a more realistic way. At present, newer and more perceptually uniform color spaces, such as SVF, 11 DIN99d, 12 and CIECAM02, 13 are available, so we are going to plot the color solid in these color spaces and analyze it with profiles of constant lightness and hue angle for several illuminants and light sources.…”

Section: Introductionmentioning

confidence: 99%

Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source

et al. 2007

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We present a systematic algorithm capable of searching for optimal colors for any lightness L * (between 0 and 100), any illuminant (D65, F2, F7, F11, etc.), and any light source reported by CIE. Color solids are graphed in some color spaces (CIELAB, SVF, DIN99d, and CIECAM02) by horizontal (constant lightness) and transversal (constant hue angle) sections. Color solids plotted in DIN99d and CIECAM02 color spaces look more spherical or homogeneous than the ones plotted in CIELAB and SVF color spaces. Depending on the spectrum of the light source or illuminant, the shape of its color solid and its content (variety of distinguishable colors, with or without color correspondence) change drastically, particularly with sources whose spectrum is discontinuous and/or very peaked, with correlated color temperature lower than 5500 K. This could be used to propose an absolute colorimetric quality index for light sources comparing the volumes of their gamuts, in a uniform color space.

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“…Table 1 also shows that WSTRESS is always lower than STRESS, which means that the average similitude between perceived (ΔV) and computed (ΔE) color differences increases when a lower weight is assigned to the color pairs with higher uncertainty in observers' visual assessments. Color-Difference Formula STRESS WSTRESS CIELUV [2] 33.4 29.7 CIELAB [3] 35.0 32.6 CMC [4] 40.8 33.8 BFD [5] 43.4 34.2 CIE94 [6] 36.2 34.2 CIEDE2000 [7,11] 32.0 28.1 DIN99d [8] 31.5 28.4 AUDI2000 [14] 27.3 23.9 CAM02-SCD [9] 28.6 24.2 CAM02-UCS [9] 29.3 24.8 OSA-GP-Euclidean [10] 40.6 31.2…”

Section: Resultsmentioning

confidence: 99%

“…For example, in the automotive industry, the different parts of cars are produced by different manufactures using different materials, and reliable color-difference formulas are necessary for automatic pass/fail color decisions. In the past years, a number of color-difference formulas have been proposed for industrial applications [2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Measuring color differences in gonioapparent materials used in the automotive industry

Melgosa

Gómez‐Robledo

Cui

et al. 2015

J. Phys.: Conf. Ser.

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Abstract. This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A colordifference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosa et al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal color vision using a set of 56 nearly achromatic color pairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.

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Uniform colour spaces based on the DIN99 colour‐difference formula

Cited by 96 publications

References 10 publications

Number of discernible colors for color-deficient observers estimated from the MacAdam limits

Number of discernible colors for color-deficient observers estimated from the MacAdam limits

Computation and visualization of the MacAdam limits for any lightness, hue angle, and light source

Measuring color differences in gonioapparent materials used in the automotive industry

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