The Experts below are selected from a list of 390 Experts worldwide ranked by ideXlab platform

B. Rigg - One of the best experts on this subject based on the ideXlab platform.

  • bfd l c Colour Difference Formula part 2 performance of the Formula
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: M R Luo, B. Rigg
    Abstract:

    The available experimental data relating to small Colour Differences between pairs of surface Colours have been combined together into two sets including perceptibility results (CP) and acceptability results (CA). A new Colour-Difference Formula, BFD(\:c) has been developed using the combined experimental results. For small Colour Differences, particularly when perceptibility judgements are involved, the new Formula represents a substantial improvement over other fomulae. For large Colour-Differences the new Formula is close to the best available Formula. Different 1 values are required for perceptibility and acceptability judgements, and for large Colour Differences, but c=1 in all cases. The BFD Formula gives the best possible results obtainable with currently available data. Analysis shows that results from different studies, including those based on perceptibility and acceptability judgements, are compatible in many respects. Discrepancies that were detected seemed to be due to experimental error, or problems in scaling the visual results. However, there are major Differences between the results for small Differences between surface Colours and those implicit in the Munsell system and MacAdam ellipses.

  • modification to the jpc79 Colour Difference Formula
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: F J J Clarke, R Mcdonald, B. Rigg
    Abstract:

    The JPC79 Colour–Difference Formula has represented a substantial improvement over earlier Formulae and is being applied successfully in industrial shade passing. Modifications are described which overcome certain problems and, to some extent, simplify the Formula. With available experimental data, the modified version performed even better than the original Formula. Perceptibility data are fitted better by increasing the JPC79 lightness weighting by a factor of two. The new Formula, designated CMC (: c), has the best overall performance of any Formula so far published.

  • a Colour Difference Formula for surface Colours under illuminant a
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: Ming Ronnier Luo, B. Rigg
    Abstract:

    The available experimental data for small Colour Differences between surface Colours under illuminant A have been analysed in a manner similar to that used earlier for the comparable results under daylight. Chromaticity discrimination ellipses were calculated from the results for each Colour centre. The size of the ellipses varied with chromaticity in an irregular manner suggesting that the visual results for the different centres were effectively on different scales. New experiments, carried out using a grey scale method for the visual assessments, allowed the relative sizes of ellipses to be adjusted. After adjustment the size of the ellipses varied much more systematically with chromaticity. Similar adjustments allowed all the results to be combined together and used to develop a new Colour-Difference Formula suitable for assessments under illuminant A. Values of ΔE from the new Formula gave a better fit to the visual results than those from other Formulae. Earlier Formulae were intended to be used with results for daylight. Using chromatic adaption Formulae to transform the illuminant A results to illuminant D65 improved the agreement, but the results were still not as good as those obtained with the new Formula.

  • uniform Colour space based on the cmc l c Colour Difference Formula
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: Ming Ronnier Luo, B. Rigg
    Abstract:

    The CMC(c) Colour-Difference Formula agrees more closely with visual assessments than does the CIE L*a*b* Formula, but hitherto there has been no associated ‘uniform Colour space’. A new Colour space similar in form to CIE L*a*b* space has been derived in which distances agree closely with the corresponding ΔE(CMC) values. The new space was extensively tested using real and hypothetical pairs of samples. In each case the distance, in the space, between a pair of samples was compared with the ΔE(CMC) value. The disagreement rarely exceeded 20%, while discrepancies between distances in CIE L*a*b* space and those implied by the CMC Formula can exceed 500%. It is easy to construct ‘micro-spaces’ apparently corresponding to the CMC Formula which should be applicable to small regions of Colour space and hence useful for applications such as Colour sorting. Such micro-spaces did not agree with the CMC Formula as well as did the new space. The new space represents a substantial improvement over CIE L*a*b* space with respect to uniformity; its form is similar to CIE L*a*b* and so is easy to use.

  • bfd l c Colour Difference Formula part 1ndashdevelopment of the Formula
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: Ming Ronnier Luo, B. Rigg
    Abstract:

    The available experimental data relating to small Colour Differences between pairs of surface Colours have been combined together into sets including perceptibility results and acceptability results. Supplementary experiments have been carried out to enable all the previous visual results to be brought on to a common scale, and to provide extra information when this was considered necessary. A new Colour-Difference Formula, BFD(l:c), has been developed using the combined experimental results. Various aspects of Colour Differences have been considered in turn to decide the form of Formula required, and the constants in the Formula have been optimised using the combined perceptibility and acceptability results. The new Formula is similar in structure to the CMC(l:c) Formula in most respects. However, it was found that a new term was required to take account of the fact that when chromaticity discrimination ellipses calculated from experimental results are plotted in a b space, they do not all point towards the neutral point. The experimental results were not very consistent with respect to possible tilting of discrimination ellipsoids relative to the xy plane. Overall it seems that any such tilting is quite small and in the direction implicit in the CMC and BFD Formulae. Experimental results based on both acceptability and perceptibility judgements form part of the same overall pattern except for the weighting of lightness Differences relative to hue and chroma Differences.

Ming Ronnier Luo - One of the best experts on this subject based on the ideXlab platform.

  • a comprehensive model of Colour appearance for related and unrelated Colours of varying size viewed under mesopic to photopic conditions
    Color Research and Application, 2017
    Co-Authors: Shou Ting Wei, Kaida Xiao, Ming Ronnier Luo, Michael R Pointer
    Abstract:

    CIE has recommended two previous appearance models, CIECAM97s and CIECAM02. However, these models are unable to predict the appearance of a comprehensive range of Colours. The purpose of this study is to describe a new, comprehensive Colour appearance model, which can be used to predict the appearance of Colours under various viewing conditions that include a range of stimulus sizes, levels of illumination that range from scotopic through to photopic, and related and unrelated stimuli. In addition, the model has a uniform Colour space that provides a Colour-Difference Formula in terms of Colour appearance parameters. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 293–304, 2017

  • Verification of CIEDE2000 using industrial data
    2015
    Co-Authors: Ming Ronnier Luo, Carl Minchew, Phil Kenyon, Guihua Cui
    Abstract:

    CIEDE2000 Colour Difference Formula was recommended by CIE in 2000 for industrial Colour Difference evaluation. A new set of paint samples was prepared and was assessed by a panel of observers from two companies and one university. The results were used to reveal observer uncertainty, to test different Colour Difference Formulae and to set each Formula’s Colour tolerance. The results show that CIEDE2000 slightly outperformed the other Formulae

  • a Colour Difference Formula for surface Colours under illuminant a
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: Ming Ronnier Luo, B. Rigg
    Abstract:

    The available experimental data for small Colour Differences between surface Colours under illuminant A have been analysed in a manner similar to that used earlier for the comparable results under daylight. Chromaticity discrimination ellipses were calculated from the results for each Colour centre. The size of the ellipses varied with chromaticity in an irregular manner suggesting that the visual results for the different centres were effectively on different scales. New experiments, carried out using a grey scale method for the visual assessments, allowed the relative sizes of ellipses to be adjusted. After adjustment the size of the ellipses varied much more systematically with chromaticity. Similar adjustments allowed all the results to be combined together and used to develop a new Colour-Difference Formula suitable for assessments under illuminant A. Values of ΔE from the new Formula gave a better fit to the visual results than those from other Formulae. Earlier Formulae were intended to be used with results for daylight. Using chromatic adaption Formulae to transform the illuminant A results to illuminant D65 improved the agreement, but the results were still not as good as those obtained with the new Formula.

  • uniform Colour space based on the cmc l c Colour Difference Formula
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: Ming Ronnier Luo, B. Rigg
    Abstract:

    The CMC(c) Colour-Difference Formula agrees more closely with visual assessments than does the CIE L*a*b* Formula, but hitherto there has been no associated ‘uniform Colour space’. A new Colour space similar in form to CIE L*a*b* space has been derived in which distances agree closely with the corresponding ΔE(CMC) values. The new space was extensively tested using real and hypothetical pairs of samples. In each case the distance, in the space, between a pair of samples was compared with the ΔE(CMC) value. The disagreement rarely exceeded 20%, while discrepancies between distances in CIE L*a*b* space and those implied by the CMC Formula can exceed 500%. It is easy to construct ‘micro-spaces’ apparently corresponding to the CMC Formula which should be applicable to small regions of Colour space and hence useful for applications such as Colour sorting. Such micro-spaces did not agree with the CMC Formula as well as did the new space. The new space represents a substantial improvement over CIE L*a*b* space with respect to uniformity; its form is similar to CIE L*a*b* and so is easy to use.

  • bfd l c Colour Difference Formula part 1ndashdevelopment of the Formula
    Journal of The Society of Dyers and Colourists, 2008
    Co-Authors: Ming Ronnier Luo, B. Rigg
    Abstract:

    The available experimental data relating to small Colour Differences between pairs of surface Colours have been combined together into sets including perceptibility results and acceptability results. Supplementary experiments have been carried out to enable all the previous visual results to be brought on to a common scale, and to provide extra information when this was considered necessary. A new Colour-Difference Formula, BFD(l:c), has been developed using the combined experimental results. Various aspects of Colour Differences have been considered in turn to decide the form of Formula required, and the constants in the Formula have been optimised using the combined perceptibility and acceptability results. The new Formula is similar in structure to the CMC(l:c) Formula in most respects. However, it was found that a new term was required to take account of the fact that when chromaticity discrimination ellipses calculated from experimental results are plotted in a b space, they do not all point towards the neutral point. The experimental results were not very consistent with respect to possible tilting of discrimination ellipsoids relative to the xy plane. Overall it seems that any such tilting is quite small and in the direction implicit in the CMC and BFD Formulae. Experimental results based on both acceptability and perceptibility judgements form part of the same overall pattern except for the weighting of lightness Differences relative to hue and chroma Differences.

Guihua Cui - One of the best experts on this subject based on the ideXlab platform.

  • Verification of CIEDE2000 using industrial data
    2015
    Co-Authors: Ming Ronnier Luo, Carl Minchew, Phil Kenyon, Guihua Cui
    Abstract:

    CIEDE2000 Colour Difference Formula was recommended by CIE in 2000 for industrial Colour Difference evaluation. A new set of paint samples was prepared and was assessed by a panel of observers from two companies and one university. The results were used to reveal observer uncertainty, to test different Colour Difference Formulae and to set each Formula’s Colour tolerance. The results show that CIEDE2000 slightly outperformed the other Formulae

  • Testing the AUDI2000 Colour-Difference Formula for solid Colours using some visual datasets with usefulness to automotive industry
    8th Iberoamerican Optics Meeting and 11th Latin American Meeting on Optics Lasers and Applications, 2013
    Co-Authors: Juan Martinez-garcia, Manuel Melgosa, Min Huang, M. Ronnier Luo, Guihua Cui, Hao-xue Liu, Luis Gomez-robledo, Thomas Dauser
    Abstract:

    Colour-Difference Formulas are tools employed in Colour industries for objective pass/fail decisions of manufactured products. These objective decisions are based on instrumental Colour measurements which must reliably predict the subjective Colour-Difference evaluations performed by observers’ panels. In a previous paper we have tested the performance of different Colour-Difference Formulas using the datasets employed at the development of the last CIErecommended Colour-Difference Formula CIEDE2000, and we found that the AUDI2000 Colour-Difference Formula for solid (homogeneous) Colours performed reasonably well, despite the Colour pairs in these datasets were not similar to those typically employed in the automotive industry (CIE Publication x038:2013, 465-469). Here we have tested again AUDI2000 together with 11 advanced Colour-Difference Formulas (CIELUV, CIELAB, CMC, BFD, CIE94, CIEDE2000, CAM02-UCS, CAM02-SCD, DIN99d, DIN99b, OSA-GP-Euclidean) for three visual datasets we may consider particularly useful to the automotive industry because of different reasons: 1) 828 metallic Colour pairs used to develop the highly reliable RIT-DuPont dataset (Color Res. Appl. 35, 274-283, 2010); 2) printed samples conforming 893 Colour pairs with threshold Colour Differences (J. Opt. Soc. Am. A 29, 883-891, 2012); 3) 150 Colour pairs in a tolerance dataset proposed by AUDI. To measure the relative merits of the different tested Colour-Difference Formulas, we employed the STRESS index (J. Opt. Soc. Am. A 24, 1823-1829, 2007), assuming a 95% confidence level. For datasets 1) and 2), AUDI2000 was in the group of the best Colour-Difference Formulas with no significant Differences with respect to CIE94, CIEDE2000, CAM02-UCS, DIN99b and DIN99d Formulas. For dataset 3) AUDI2000 provided the best results, being statistically significantly better than all other tested Colour-Difference Formulas.

  • Colour Difference Evaluation
    Advanced Color Image Processing and Analysis, 2012
    Co-Authors: Manuel Melgosa, Alain Trémeau, Guihua Cui
    Abstract:

    For a pair of homogeneous Colour samples or two complex images viewed under specific conditions, Colour-Difference Formulas try to predict the visually perceived (subjective) Colour Difference starting from instrumental (objective) Colour measurements. The history related to the five up-to-date CIE-recommended Colour-Difference Formulas is reviewed, with special emphasis on the structure and performance of the last one, CIEDE2000. Advanced Colour-Difference Formulas with an associated Colour space (e.g., DIN99d, CAM02, Euclidean OSA-UCS, etc.) are also discussed. Different indices proposed to measure the performance of a given Colour-Difference Formula (e.g., PF/3, STRESS, etc.) are reviewed. Among current trends on Colour-Difference evaluation, it can be mentioned the research activities carried out by different CIE Technical Committees (e.g., CIE TC’s 1-55, 1-57, 1-63, 1-81 and 8-02), the need of new reliable experimental datasets, the development of Colour-Difference Formulas based on IPT and Colour-appearance models, and the concept of “total Differences,” which considers the interactions between Colour properties and other object attributes like texture, translucency, and gloss.

  • Assessing Colour Differences with different magnitudes
    2004
    Co-Authors: Guihua Cui, Ming Ronnier Luo, B. Rigg
    Abstract:

    The CIEDE2000 Colour Difference Formula recommended by the CIE in 2000 is mainly used for evaluating small size Colour-Differences (less than 5 *abE ∆ units). This study is intended to investigate the performances of this Formula together with the others in predicting a newly accumulated experimental data set having a wide range of Colour Differences. The data included 4 subsets: surface textile samples, and CRT Colours with small, medium and large magnitudes. Each subset had 62 pairs surrounding 5 Colour centers

  • uniform Colour spaces based on the din99 Colour Difference Formula
    Color Research and Application, 2002
    Co-Authors: Guihua Cui, Ming Ronnier Luo, B. Rigg, G Roesler, Klaus Witt
    Abstract:

    Several Colour-Difference Formulas such as CMC, CIE94, and CIEDE2000 have been developed by modifying CIELAB. These Formulas give much better fits for experimental data based on small Colour Differences than does CIELAB. None of these has an associated uniform Colour space (UCS). The need for a UCS is demonstrated by the widespread use of the a*b* diagram despite the lack of uniformity. This article describes the development of Formulas, with the same basic structure as the DIN99 Formula, that predict the experimental data sets better than do the CMC and CIE94 Colour-Difference Formulas and only slightly worse than CIEDE2000 (which was optimized on the experimental data). However, these Formulas all have an associated UCS. The spaces are similar in form to L*a*b*. © 2002 Wiley Periodicals, Inc. Col Res Appl, 27, 282–290, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10066

Manuel Melgosa - One of the best experts on this subject based on the ideXlab platform.

  • revisiting the weighting function for lightness in the ciede2000 Colour Difference Formula
    Coloration Technology, 2017
    Co-Authors: Manuel Melgosa, Claudio Oleari, Pedro J Pardo, Min Huang, Changjun Li
    Abstract:

    We have used 13 experimental datasets (7420 Colour pairs) to study the performance of the weighting function for lightness proposed by the CIEDE2000 Colour-Difference Formula, because it has been suggested that this function can be improved by using the weighting function for lightness SL = 1 adopted by the CIE94 Colour-Difference Formula. Using the standardised residual sum of squares (STRESS) index, it was found that: (i) replacing the SL in CIEDE2000 with SL = 1 improved the results for 7/13 datasets considered, but the improvement was statistically significant only for 1/13 datasets; (ii) a Whittle-type lightness-Difference Formula can be used to replace the term ∆L*/SL in CIEDE2000, which led to a new Colour-Difference Formula with no statistically significant Difference with respect to CIEDE2000 for any of the 13 experimental datasets. A modification of the CIEDE2000 Formula using a Whittle-type lightness Formula is proposed.

  • Testing the AUDI2000 Colour-Difference Formula for solid Colours using some visual datasets with usefulness to automotive industry
    8th Iberoamerican Optics Meeting and 11th Latin American Meeting on Optics Lasers and Applications, 2013
    Co-Authors: Juan Martinez-garcia, Manuel Melgosa, Min Huang, M. Ronnier Luo, Guihua Cui, Hao-xue Liu, Luis Gomez-robledo, Thomas Dauser
    Abstract:

    Colour-Difference Formulas are tools employed in Colour industries for objective pass/fail decisions of manufactured products. These objective decisions are based on instrumental Colour measurements which must reliably predict the subjective Colour-Difference evaluations performed by observers’ panels. In a previous paper we have tested the performance of different Colour-Difference Formulas using the datasets employed at the development of the last CIErecommended Colour-Difference Formula CIEDE2000, and we found that the AUDI2000 Colour-Difference Formula for solid (homogeneous) Colours performed reasonably well, despite the Colour pairs in these datasets were not similar to those typically employed in the automotive industry (CIE Publication x038:2013, 465-469). Here we have tested again AUDI2000 together with 11 advanced Colour-Difference Formulas (CIELUV, CIELAB, CMC, BFD, CIE94, CIEDE2000, CAM02-UCS, CAM02-SCD, DIN99d, DIN99b, OSA-GP-Euclidean) for three visual datasets we may consider particularly useful to the automotive industry because of different reasons: 1) 828 metallic Colour pairs used to develop the highly reliable RIT-DuPont dataset (Color Res. Appl. 35, 274-283, 2010); 2) printed samples conforming 893 Colour pairs with threshold Colour Differences (J. Opt. Soc. Am. A 29, 883-891, 2012); 3) 150 Colour pairs in a tolerance dataset proposed by AUDI. To measure the relative merits of the different tested Colour-Difference Formulas, we employed the STRESS index (J. Opt. Soc. Am. A 24, 1823-1829, 2007), assuming a 95% confidence level. For datasets 1) and 2), AUDI2000 was in the group of the best Colour-Difference Formulas with no significant Differences with respect to CIE94, CIEDE2000, CAM02-UCS, DIN99b and DIN99d Formulas. For dataset 3) AUDI2000 provided the best results, being statistically significantly better than all other tested Colour-Difference Formulas.

  • Colour Difference Evaluation
    Advanced Color Image Processing and Analysis, 2012
    Co-Authors: Manuel Melgosa, Alain Trémeau, Guihua Cui
    Abstract:

    For a pair of homogeneous Colour samples or two complex images viewed under specific conditions, Colour-Difference Formulas try to predict the visually perceived (subjective) Colour Difference starting from instrumental (objective) Colour measurements. The history related to the five up-to-date CIE-recommended Colour-Difference Formulas is reviewed, with special emphasis on the structure and performance of the last one, CIEDE2000. Advanced Colour-Difference Formulas with an associated Colour space (e.g., DIN99d, CAM02, Euclidean OSA-UCS, etc.) are also discussed. Different indices proposed to measure the performance of a given Colour-Difference Formula (e.g., PF/3, STRESS, etc.) are reviewed. Among current trends on Colour-Difference evaluation, it can be mentioned the research activities carried out by different CIE Technical Committees (e.g., CIE TC’s 1-55, 1-57, 1-63, 1-81 and 8-02), the need of new reliable experimental datasets, the development of Colour-Difference Formulas based on IPT and Colour-appearance models, and the concept of “total Differences,” which considers the interactions between Colour properties and other object attributes like texture, translucency, and gloss.

  • fuzzy analysis for detection of inconsistent data in experimental datasets employed at the development of the ciede2000 Colour Difference Formula
    Journal of Modern Optics, 2009
    Co-Authors: Samuel Morillas, Rafael Huertas, Luis Gomezrobledo, Manuel Melgosa
    Abstract:

    Relating instrumental measurements to visually perceived Colour-Differences, under specific illuminating and viewing conditions, is one of the challenges of advanced colorimetry. Experimental data are used to devise new Colour-Difference Formulas as well as to assess the performance of other Colour-Difference Formulas. In this paper, we analyse the consistency of experimental data employed at the development of the last CIE recommended Colour-Difference Formula, CIEDE2000. Because of the subjective and imprecise nature of these data, we adopt a fuzzy approach, so that finally, for each experimental datum, we establish the fuzzy degree to which it can be considered consistent with the remaining data. The results of our analyses show that only a few data are associated with a rather low degree of consistency. These data in many cases correspond to Colour pairs with a very small Colour-Difference for which visual assessments seem to be overestimated.

Ronnier M Luo - One of the best experts on this subject based on the ideXlab platform.

  • optimisation of food expectations using product Colour and appearance
    Food Quality and Preference, 2012
    Co-Authors: Shuoting Wei, Ronnier M Luo, John B Hutchings
    Abstract:

    Abstract This paper describes a method for quantifying food appearance and studies the relationship between Colour appearance and sensory characteristics of expected levels. Orange juice is used as an example. An experiment involving visual assessments was carried out using a calibrated digital display. The first phase of the experiment (i.e. Phase I) focused on investigating tolerance for Colour as an orange juice attribute and the second phase (i.e. Phase II) concentrated on relationships between juice Colours and expected sensory characteristics. Visual judgements were made of sourness, sweetness, bitterness, flavour strength and freshness. In Phase I, 174 juice Colours were rendered systematically in CIELAB Colour space and assessed by 15 observers. It was found that Colour tolerance of orange juices can be determined using the CIELAB Colour Difference Formula ( Δ E ab ∗ ). A Colour will be accepted by the majority as natural orange juice if its Colour Difference against an ideal juice Colour is smaller than 12.60 Δ E ab ∗ units, where the lightness, chroma and hue of the ideal orange juice Colour was 67, 62 and 88°, respectively. In Phase II, observers were asked to assess the same panel of stimuli using the expected levels of the five sensory characteristics. It was found that greenish juice Colours elicited greater sourness and bitterness responses. Darker juice Colours were more likely to be expected to be bitter, and redder and yellower juice Colours were expected to be sweeter and have stronger flavour. Fresher juices were distributed within the region of saturated yellow. These relationships were described by means of Δ E ab ∗ which reasonably explains the relationships except the cases of sourness (R2 = 0.66) and freshness (R2 = 0.66). A new Colour Difference Formula ΔEOJ was proposed and this Formula effectively improved the performance of predictions for sourness (R2 = 0.72) and freshness (R2 = 0.82). The methodology developed in this study includes a systematic study to find the “ideal” Colour appearance of a particular food, application of the psychophysical method for assessing expected levels of different sensory characteristics and a method for modelling the appearance and expectation relationships. This methodology can be widely applied to optimise visually perceived expectations for other foods and products that are sensitive to visual judgements of quality.

  • investigation of parametric effects using medium Colour Difference pairs
    Color Research and Application, 2001
    Co-Authors: John Haozhong Xin, Chuen Chuen Lam, Ronnier M Luo
    Abstract:

    The article investigates five types of parametric effects in assessing Colour Difference. The visual assessment experiments were conducted in six phases. The viewing parameters studied include the sample separation, sample size, and the background Colours. The dataset prepared in this study includes a total of 107 cotton-dyed pairs belonging to five Colour centers. The average Colour Difference of the sample pairs was about 5.0 CIELAB units. Gray-scale method was used for Colour-Difference assessment with a panel of 10 observers (2 assessments each). The CIELAB Colour-Difference Formula was found to have the best performance over other Formulae using the current dataset. In general, the parametric effects vary from 8–15%. When further analyzing the Colour centers, it was found that much larger parametric effects of 42% and 26% were associated, respectively, with green sample pairs assessed on the green background and blue samples pairs assessed on the blue background. The green and blue background Colours in these two cases are very close to the green and blue Colour centers selected, which clearly indicates the crispening effect. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 376–383, 2001

  • a Colour Difference Formula for assessing large Colour Differences
    Color Research and Application, 1999
    Co-Authors: Shing Sheng Guan, Ronnier M Luo
    Abstract:

    An experiment was carried out to study large Colour Differences. Two-hundred-and-ninety-two wool pairs were prepared with an average Difference of 12 CIELAB ΔE units. Visual assessments were conducted using gray scale and pair comparison psychophysical methods by a panel of 20 observers. The results from the two psychophysical methods were used to test Colour-Difference Formulae and compare their Differences. The gray scale results were also used to compare with the other large Colour-Difference data sets, i.e., BFB, OSA, and WW. The present results together with part of the other data sets were combined to form a single data set. A modified CIELAB Colour-Difference Formula was developed having a structure similar to that of CIE94. It is named the GLAB Colour-Difference Formula. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 344–355, 1999