Colour difference detection algorithm for warp‐knitted fabric based on image colour appearance model

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 color- difference 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 [Melgosaet 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 colorvision using a set of 56 nearly achromatic colorpairs 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.

In meetings just prior to the 1997 AIC Congress in Kyoto, CIE TC1-37, chaired by M. Fairchild, established the CIE 1997 Interim Colour appearance Model (Simple Version), known as CIECAM97s. CIECAM97s was formally published in 1998 in CIE publication 131. CIE TC1-37 was dissolved shortly after publication of CIECAM97s at which time, a reportership, R1- 24 held by M. Fairchild, was established to monitor ongoing developments in color appearance modeling and notify CIE Division 1 if it became necessary to form a new TC to consider revision or replacement of CIECAM97s. In the four years between AIC Congresses, there has been much activity, both by individual researchers and within the CIE, aimed at furthering our understanding of color appearance models and deriving improved models for consideration. The aim of this paper is to summarize these activities, report on the current status of CIE efforts on color appearance models, and suggest what the future might hold for CIE color appearance models.

A comprehensive colour appearance model should be capable of predicting a wide range of viewing conditions including related and unrelated colours under a wide range of illuminance levels from mesopic to photopic region. In the past, colour appearance models can only predict the colour appearance for related colours in different viewing conditions. More recently, colour appearance models to predict unrelated colours have been developed and being improved constantly. This paper investigates the performance of different colour appearance models for unrelated colours. The three colour appearance modelswere compared including CAM15u, CAMFu and the latest CAM20u. An experimental dataset carefully accumulated by Fu et al. was used for evaluation. The results showed that the latest CAM20u performed best among the three models. CAMFu, as the oldest model, whose performance was much worse than other two models in predicting brightness and colourfulness, and performed well in predicting hue composition, while CAM15u gave a moderate performance in predicting brightness and colourfulness, but performed a little worse than the others for hue composition.

Regarding the ocean background, the painted camouflage on the surface of targets effectively conceals them, providing a strategic defense against military reconnaissance. Accurately predicting the color appearance of both the target and background is crucial for assessing the camouflage’s performance. This study investigates the perceived color attributes (lightness, chroma, and hue) of marine targets against varying ocean backgrounds using memory matching assessments. Visual data reveal that background color slightly influences target hue perception through simultaneous contrast effects, while lightness and chroma remain unaffected. As the image-based color appearance model – iCAM offers a potential solution for extracting color appearance attributes from a complex RGB image, it has been adopted to predict the pixel-wise color appearance of the marine targets. Comparative validation shows iCAM substantially outperforms existing color appearance models in marine environments, establishing its superior capability for naval camouflage assessment and design. Further analysis indicates that chroma predictions are sensitive to changes in the filter kernel size of iCAM and the image size, while lightness and hue predictions remain stable. Notably, undersized kernels systematically underestimate perceived chroma, highlighting the critical importance of parameter optimization.

Tourmaline minerals are mainly produced in pegmatite, which is mainly produced in pegmatite.At present, the color evaluation of green tourmaline in China needs to be supplemented. In this paper, the CIECAM16 color appearance model is used to calculate the color appearance attribute parameters of green tourmaline samples, and the tristimulus XYZ of green tourmaline color measured by Colori5 colorimeter is used as the input data of CIECAM16 color appearance model to predict the color appearance attribute of green tourmaline under different conditions. The CIECAM16 color appearance model written by computer C++ language is used to calculate the color appearance attribute parameters under different illuminance levels under D65 light source, different environment (Average, Dim, Dark) conditions and different illumination light source color temperatures (D65, D50, A). Through analysis and calculation of the color appearance attribute parameters, it is found that that the increase of illuminance has a more intuitive effect on the visual brightness Q, while the change of ambient light and shade has a greater effect on the brightness than the change of light source. The A light source has a more obvious effect on the tourmaline of color than D65 and D50 light sources.

Some of the reasons for needing a color appearance model in imaging are given and the use of such a model in deriving a color reproduction index is described. There are three reasons why a model of color appearance is a necessary tool in color imaging systems. First, because the viewing conditions for images are often different at different stages of reproduction systems, it is necessary to allow for their visual effects; conventional colorimetry does not do this, but a model of color appearance can supply the necessary adjustments. Second, different display media typically have different color gamuts and a regime of gamut mapping is therefore often required; it is more appropriate to conduct this mapping in an appearance space. Third, it is desirable to be able to assess the quality of color reproductions in terms of a color reproduction index and a model of color appearance can provide a metric that is suitable as the basis of such an index.

Application of the CIECAM02 colour appearance model to predict the effect of gamma on the colours viewed on CRT monitors

In this paper, the influence of neutral backgrounds with different lightness on color appearance was studied, five color centers and nine neutral backgrounds with different lightness based on printed samples were prepared. 20 observers were organized to carry out visual experiment with the method of paired comparison. The obtained experimental results indicate that the color appearance of color center is more affected by higher lightness backgrounds than the lower, which is quite different with the results computed by color appearance models (CAM). Furthermore, the factor of Standardized Residual Sum of Squares (STRESS) was used to evaluate the performance of CAM16 and CAM02 model. The STRESS values show that CAM16 (37.22) predicted more close to the visual results and performed well comparing with CAM02 (44.00).

Color-normal subjects sometimes disagree about metameric matches involving highly structured SPDs, because their cone fundamentals differ slightly, but non-negligibly. This has significant implications for the design of light sources and displays, so it should be estimated. We propose a broadly applicable estimation method based on a simple adaptive "front-end" interface that can be used with any selected standard color appearance model. The interface accepts, as input, any set of color matching functions for the individual subject (for example, these could be that person's cone response functions) and also the associated tristimulus values for the test stimulus and also for the reference stimulus (i.e. reference white). The interface converts this data into tristimulus values of the form used by the selected color appearance model (which could, for example, be X, Y, Z), while also carrying out the needed transform, which is based on an estimate of the subject's likely previous long-term adaptations to their unique cone fundamentals. The selected standard color appearance model then provides color appearance data that is an estimate of the color appearance of the test stimulus, for that individual subject. This information has the advantage of being interpretable within that model's well-known color space. The adaptive front end is based on the fact that, for any selected input SPD and the subject's unique color matching functions, there can be many different SPDs that are metameric for that individual. Since observer-to-observer color perception differences are minimized for spectrally smooth SPDs, smooth metamers predict color appearances reasonably accurately.

Fifty-four spectral reflectances of skin colors (facial pattern of Japanese women) were measured and analyzed by the principal component analysis. The results indicate that the reflectance spectra can be estimated approximately 99% by only three principal components. Based on the experimental results, it is shown that the spectral reflectance of all pixels in skin can be calculated from the R, G, B signals of HDTV (High Definition Television) camera.Computer simulations of color reproduction in skin color have been developed in both colorimetric color reproduction and color appearance models by von Kries, LAB and Fairchild. The obtained color reproduction in facial pattern and skin color patch under different illuminants are analyzed. Those reproduced color images were compared by memory matching method. The difference of appearance models is described and the difference of appearance between skin color patch and facial pattern is also discussed and analyzed.

The sunglass industry has seen a major development in the past few years, though without the development of sunglass simulation tools for the wearers. This study describes a protocol to accurately simulate sunglass filtered vision using hyperspectral imaging and colour appearance model. The use of hyperspectral imaging ensures that the spectral transmittances of the sunglasses can be applied to the spectral radiances of the target scene. This filtered hyperspectral data can then be converted into a colour image using CIE XYZ tristimulus values and image colour appearance model (iCAM06). The study also identifies the protocol for the testing of these filtered images through psychophysical experiments and formulates the key parameters for testing. Furthermore, the study also categorizes the acquisition parameters for accurate and fast application of sunglasses on hyperspectral images. Objective testing on the optimized hyperspectral data revealed a reduction of data size by four times, without any loss of colorimetric accuracy. The study lays out a clear path for the future execution of psychophysical experiments to validate the accuracy of reproduction for these simulated images.

This paper describes physical measures for quantifying the quality of light sources and their characteristics. Typical light sources, including incandescent lamps, fluorescent lamps and light emitting diodes, are first introduced and their performance is compared. The CIE colour specification system is then described, including physical quantities for specifying light sources such as colour temperature, spectral power distribution, luminance, illuminance, luminous efficacy, chromaticity coordinates, uniform colour spaces, a colour difference formula and a colour appearance model. Finally, the CIE colour rendering index, together with recent developments towards a new index, including CRI‐CAM02UCS, is described.

The conventional object segmentation methods often degrade their performance due to the requirement of user interaction and/or the incomplete colour appearance models. In this Letter, the authors propose a novel design method of a colour appearance model for accurate and fully‐automatic object segmentation by using saliency maps. The authors initialise the Gaussian mixture models (GMMs) to describe the colour appearance of the foreground objects and the background, respectively, where the mean vectors, covariance matrices, and mixing coefficients are updated adaptively such that more salient pixels have larger weights to update the GMM for the foreground objects while less salient pixels have larger weights to update the GMM for the background, respectively. Experiments are performed on MSRC, iCoseg, and PASCAL datasets and we show that the proposed method outperforms the existing methods quantitatively and qualitatively.

In this study, Swedish Natural Color System (NCS) unique hue data were used to evaluate the performance of unique hue predictions by the CIECAM02 colour appearance model. The colour appearance of 108 NCS unique hue stimuli was predicted using CIECAM02, and their distributions were represented in a CIECAM02 ac–bc chromatic diagram. The best‐fitting line for each of the four unique hues was found using orthogonal distance regression in the ac–bc chromatic diagram. Comparison of these predicted unique hue lines (based on the NCS data) with the default unique hue loci in CIECAM02 showed that there were significant differences in both unique yellow (UY) and unique blue (UB). The same tendency was found for hue uniformity: hue uniformity is worse for UY and UB stimuli in comparison with unique red (UR) and unique green (UG). A comparison between NCS unique hue stimuli and another set of unique hue stimuli (obtained on a calibrated cathode ray tube) was conducted in CIECAM02 to investigate possible media differences that might affect unique hue predictions. Data for UY and UB are in very good agreement; largest deviations were found for UR. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 256–263, 2015

Color appearance of images on self-luminous displays, such as LCD monitors, depends on two sources of illumination: scene illumination within the image itself and ambient illumination in the viewing environment. Color appearance models (CAMs) attempt to predict how perception changes as ambient illumination changes. At their best they provide viewers with an illumination-independent viewing experience. However, existing CAMs are complex and application-specific. Thus they are poorly suited to adaptive displays. For example, existing adaptive displays provide only achromatic adaptation, limiting the complexity of CAMs and minimizing tuning. We propose a new model based on von Kries adaptation, the theory on which most CAMs are based upon. It takes into account the mixed adaptation state produced by self-luminous displays. Compared to existing CAMs, our model is simpler and more efficient, yet shares the generic features of more complex CAMs.