Investigation of parametric effects using small colour differences

Guan, Shing–Sheng; Luo, M. Ronnier

doi:10.1002/(sici)1520-6378(199910)24:5<331::aid-col5>3.3.co;2-0

Cited by 14 publications

(26 citation statements)

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“…Following the same strategy as earlier authors, the best coefficients c i must minimize the value of the performance factor, 24,28 which measures the goodness of fit. For a perfect agreement between the visual results and predictions, CV and V AB should equal zero, gamma should equal one and so the performance factor should be zero.…”

Section: New Attd05-based Uniform Colour Spacementioning

confidence: 99%

“…To test the colour difference formula, we have used two datasets to calculate two parameters, which are useful to compare predictions made with our colour difference formula and with other models. These parameters are the performance factor, 24,28 (PF/3) and the standardized residual sum of squares 37 (STRESS). Both are used to compare models, but the main difference between PF/3 and STRESS is that PF/3 only evaluates the agreement between experimental and theoretical colour differences but cannot indicate the statistical significance of the difference between two colour difference formulas or spaces tested.…”

Section: Testing the Colour-difference Equation For Attd05mentioning

confidence: 99%

“…The minimization of the performance factor 28 (PF/3), which is a statistical parameter that measures the goodness of fit, was used to calculate these free parameters to fit small-magnitude and large-magnitude difference datasets. These datasets are the same used by Luo et al 23,24 The small-magnitude colour differences (SCD) were used to develop the CIE 2000 colour difference formula CIEDE2000.…”

Section: Introductionmentioning

confidence: 99%

“…35,36 Finally, we compared colour differences predicted by both models with perceptual colour differences. For that, we calculated the performance factor 28 (PF/3) and the standardized residual sum of squares 37 (STRESS), which are used to compare different models 28,29,38 and so we can decide which model better predicts perceptual colour differences.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing the metrics of the perceptual space in a new multistage physiological colour vision model

Chorro¹,

Verdú²,

Sáiz³

et al. 2009

Color Research & Application

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In this work, the metric of a new multistage colour vision model, ATTD05, is assessed and a new colour difference formula is suggested. Firstly, the uniformity of the ATTD05 colour space was compared with that of CIECAM02 for some Munsell samples, because if the model yields a uniform perceptual space, we will be able to implement a colour difference formula as a Euclidian distance between two points. Secondly, we developed a new space based on the perceptual descriptors of the model: brightness, hue, colourfulness, and saturation. After that, we calculated the free parameters of the space that better fit the measured and experimental data of two datasets (small-magnitude and large-magnitude colour differences), by minimizing the performance factor (PF/3). Finally, we compare colour differences calculated for ATTD05 and for other models. The PF/3 and the STRESS parameters were used to decide which model predicts better perceptual differences and, therefore, which model was the more uniform.

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Section: New Attd05-based Uniform Colour Spacementioning

confidence: 99%

Section: Testing the Colour-difference Equation For Attd05mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analyzing the metrics of the perceptual space in a new multistage physiological colour vision model

Chorro¹,

Verdú²,

Sáiz³

et al. 2009

Color Research & Application

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“…Available thresholds for acceptable colour differences were limited to translucent rigid dental materials, fabrics, paints and dyes, but not for application in hand prosthetics (Ruyter et al 1987;Seghi et al 1989;Guan and Luo, 1999). In the absence of an established clinical colour benchmark for silicone prostheses, accurate colour simulation of the natural skin presents a constant dilemma to the clinical prosthetist.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Colour Differences in Silicone Hand and Digit Prostheses

Leow

Lee

et al. 2006

Prosthetics &Amp; Orthotics International

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This study addresses the dilemma of initial clinical and social acceptance of a newly fabricated silicone prosthesis in relation to its colour match to the natural skin. This was achieved by derivation of specific colour difference thresholds defining perceptible and acceptable levels of colour sensitivity. Two separate sets of 10 fair and dark shade digit prosthesis samples were each fabricated with a stepped increase in colour difference (DE) against the baseline hand prosthesis. Ninety individuals with normal colour vision scores were selected as colour assessors. The colour difference of each prosthesis in the two series was evaluated visually against the baseline by the assessors, using defined scores. The thresholds for perceptible and acceptable colour difference determined in this study were DE ¼ 0.8 and DE ¼ 1.8 for the fair series and DE ¼ 1.3 and DE ¼ 2.6 for the dark series, respectively. The acceptable threshold values differed from the perceptible threshold values by DE ¼ 1.0 for the fair-shade samples and DE ¼ 1.3 for the dark-shade samples. This study demonstrated that subjective visual assessment is positively correlated with DE values computed from colorimetric measurements for both fair and dark-shade silicone samples (p50.001). This results shows that human subjects with normal colour vision are capable of accurately assessing colour differences. These observations emphasize the importance of subjective feedback on colour by the patient, provided the latter has perfect colour-tested vision. The study also showed that human subjects were less sensitive to perceived colour differences in darker-shade than fairer-shade samples (p50.001). This finding seems relevant in a clinical setting involving a multi-ethnic patient population.

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Evaluation of the quality of different D65 simulators for visual assessment

Lam

Xin

2002

Color Research & Application

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Investigation of parametric effects using small colour differences

Cited by 14 publications

References 0 publications

Analyzing the metrics of the perceptual space in a new multistage physiological colour vision model

Analyzing the metrics of the perceptual space in a new multistage physiological colour vision model

Assessment of Colour Differences in Silicone Hand and Digit Prostheses

Evaluation of the quality of different D65 simulators for visual assessment

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