Bridging Color Standards: Aligning the Color‐Aid System with the International Commission on Illumination ( CIE ) and the Munsell Book of Color Coordinates

The camera output RGB signals do not directly corresponded to the tristimulus values based on the CIE standard colorimetric observer, i.e., it is a device-independent color space. For achieving accurate color information, we need to do color characterization, which can be used to derive a transformation between camera RGB values and CIE XYZ values. In this paper we set up a Back-Propagation (BP) artificial neutral network to realize the mapping from camera RGB to CIE XYZ. We used the Munsell Book of Color with total number 1267 as color samples. Each patch of the Munsell Book of Color was recorded by camera, and the RGB values could be obtained. The Munsell Book of Color were taken in a light booth and the surround was kept dark. The viewing/illuminating geometry was 0/45 using D₆₅ illuminate. The lighting illuminating the reference target needs to be as uniform as possible. The BP network was a 5-layer one and (3-10-10-10-3), which was selected through our experiments. 1000 training samples were selected randomly from the 1267 samples, and the rest 267 samples were as the testing samples. Experimental results show that the mean color difference between the reproduced colors and target colors is 0.5 CIELAB color-difference unit, which was smaller than the biggest acceptable color difference 2 CIELAB color-difference unit. The results satisfy some applications for the more accurate color measurements, such as medical diagnostics, cosmetics production, the color reappearance of different media, etc.

We had hitherto no suitable method to measure or notate the color grades of inland waters, especially of the extremely eutrophic ones like the piscicultureponds. The FOREL-ULE'S color standards do not agree with the actual water-colors, and the method by the platinum-cobalt standard, which can express exactly the brownish waters, is ineffective to other colors.In the recent time, YAMAZAKI and WATANABE reported a new colorimetric method which can indicate the three values of the C. I. E. color language, in combination with the principle of “MAXWELL's disc”. While this method has a merit in its exactness, it seems to involve a complicated treatment. In general, it seems to be more convenient in measuring and denoting the color grades by direct comparison with the standard papers.Now, the MUNSELL Book of Color provides an orderly arrangement of standard papers which serve as guide for the measurement and notation of all colors, and, in addition, it has the characteristics in that these standards represent equally spaced divisions of the three attributes of color, known in the MUNSELL System of Color Notation as Hue, Value and Chroma.By using the MUNSELL Book of Color, we can easily and quickly specify and notate the color of a substance by simple numerals, instead of obscure, nonrelated, customary name of color, and can also let it know internationally. Strictly speaking, the MUNSELL Color System is a method for the notation of the surface color of substances, but is impossible to use for either the color of a liquid or the source of light. This method can, however, be employed in the case under consideration, because the water-color of pisciculture-ponds is the characteristic “Vegetätionsfarbung”, which is caused chiefly by the thriving of phytoplankton, etc., and can be considered as a sort of surface color.In 1955, the author has measured and recorded the water-color of eel-cultureponds in the Tokai region by using the MUNSELL Book of Color. By these records, he has investigated the seasonal variation of water-color, the comparison of water-colors of fish-ponds in different districts, the relationship between the water-color and the salinity of the pond-water, and also the relationship between the composition of phytoplankton and the water-color respectively. The results obtained are as follows : (1) Seasonal variation of the water-colors of the ponds in the Izumi district is shown in Table 1, in which the maximum value of Hue, 35.0 (5.0 BG), in August, is recorded.(2) The Hue value was usually very high in the ponds in both the Kawajiri and Hamana districts (both in Shizuoka Pref.), considerably high in those in various districts of Aichi Pref., and the lowest (30.0 in average) in the ponds in Mié Pref.(3) As shown in Fig. 2, there was a clear tendency that the higher the salinity of pond-water, the lower the Hue value of the water-color.(4) While the blue-green algae, such as Microcystis, Oscillatoria, etc., are the source of the higher Hue value, as 37.5-40.0 (distinct bluish green coloration), the green algae (Scenedesmus and others) show the tendency to manifest a little lower Hue value, as 30.0-35.0 (green or yellowish green coloration). There is also a tendency that the predominance of green algae and in particular the planktonic diatoms reduces not only the Hue but also the Value and Chroma.

This empirical study had three goals: (a) to describe Somali color naming and its motifs, (b) to relate color naming by Somali informants to their color vision, and (c) to search for historical and demographic clues about the diversity of Somali color naming. Somali-speaking informants from Columbus, Ohio provided monolexemic color terms for 83 or 145 World Color Survey (WCS) color samples. Proximity analysis reduced the 103 color terms to the eight chromatic color meanings from the WCS plus black, white, and gray. Informants' data sets were grouped by spectral clustering analysis into four WCS color naming motifs named after the terms for the cool colors: (a) Green-Blue, (b) Grue (a single term meaning "green or blue"), (c) Gray, and (d) Dark. The results show that, first, the Somali language has about four motifs among its speakers. Second, individuals' color vision test results and their motifs were not correlated, suggesting that multiple motifs do not arise from individual variation in color vision. Last, the Somali color lexicon has changed over the past century. New color terms often came from the names of familiar colored objects, and informants' motifs were closely related to their ages and genders, suggesting that the diversity of color naming across speakers of Somali probably results from ongoing language change.

The current colour system for printing specifies colours using percentages of dot areas of each primary colour, i.e. cyan, magenta, yellow and black. However, this system does not conform with the colour measurement system that relates to additive colour-mixing with red, green and blue as primaries. Thus, a colour system based on colour perception of prints will provide better correlation between the colour measurement system and the printing system. This study proposed colour strength as the colour perception parameter used to connect these two systems. The aim of this study was to devise a colour system based on colour perception for primary colours in printing. The relationships between the dot area percentages of primary colours and colour strength were obtained through a series of experiments. The colour samples were printed with the offset printing system. The colour strength values of the grey samples in the reference scale were quantified by the magnitude estimation method. For the primary colour samples (C, M, and Y), the colour strength values were obtained from matching the samples to the reference scale. The second-order polynomial equations for computing the colour strength value from the dot area percentage of C, M, Y, and K and vice versa were derived. The colour strength values obtained from these equations and CIEL*a*b* values were used to derive the colour strength model. The colour system proposed in this study used CIEL*a*b* values as the input data to predict the colour strength values, then from the colour strength values to predict the dot area percentages of primary colours. The performance of the system was tested with secondary colour samples (RGB). It was found that the percentages of colour strength prediction errors for red, green and blue were 15.92, 14.07 and 43.10, respectively. The percentages of %dot area prediction errors for red, green and blue were 6.28 (average errors of Y and M), 3.90 (Y and C) and 3.28 (C and M), respectively. Since the agreements between observers’ visual data of colour strength were approximately 20% errors, the proposed colour system was considered to give good predictions.

The color depth, an important attribute of color, can reflect the amount of dye partly, which has important functions on the evaluation of color‐fastness and strength of dyes, dyeing effect of fabric, computer color matching, and so on. Natural Color System, an internationally accepted color system, orders colors by three parameters (blackness, chromaticness, and hue). The color depth has not been specified within the Natural Color System. This article tries to find the regularity of the sample with equal‐depth in Natural Color System. Firstly, 1950 color samples in Natural Color System were measured using an X‐Rite Color i7 Spectrophotometer, and their color depths were calculated by five color depth formulas. Then, trend analysis and mathematical modeling methods were used to achieve the connection between the color depth and the notations of Natural Color System basing on color depth theories. Results show that, in Natural Color System, the color samples with the same distance to pure white do not have equal depth; but the color samples with the same nuance (equal blackness, whiteness and chromaticness) have broadly equal color depth, and their average coefficient values are lower than that of Society of Dyers and Colourists Standard Depths. Besides, regressive formulas were built, with which the color depths of any chips in Natural Color System can be calculated broadly by their notation.

This is a study of perception of negative afterimages. Surface color samples were viewed under Spectralight. Subjects fixated on 11 Munsell hues mounted on white cards and matched their afterimages with chips from the Munsell Book of Color. Samples were drawn from 125 participants in two groups, one practiced, the other unfamiliar with afterimage. No single afterimage or Munsell color chip was reported for any of the stimulus hues. However, most afterimage responses for nine stimulus colors fell within one Munsell hue family. Afterimages reported for the remaining two stimulus colors of purple-blue and yellow-red span two adjacent hue families. Results suggest new alternatives to traditional subtractive color complements. New afterimage opposites are provided.

A novel general transformation between reflectance spectra and the corresponding coordinates of the Munsell Color System is presented. The coefficient values of the transformation were experimentally determined by mapping the actual reflectance spectra of the chips in the Munsell Book of Color into the Munsell Color Order System and by minimizing the distance between calculated and actual coordinates. The experiment was repeated with a selected set of points of the Munsell Renotation System. Both the Smith–Pokorny functions and the CIE 1931 standard color‐matching functions were used as a basis of the transformation. There is a good correspondence between calculated and actual coordinates of the Munsell Color System. It is also shown that the linear part of the same transformation applied to the basis functions results in one achromatic response function and two chromatic response functions in accordance with the opponent‐colors theory. © 2005 Wiley Periodicals, Inc. Col Res Appl, 31, 57–66, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20173

Fifteen ceramic gingival samples: A proposed gingival shade guide

The impact of correlated colour temperature variation from a tuneable LED lamp on colour sample appearance shift in CIELAB colour space

This report discusses two projects: developing an Illumination Testing Facility for precise solar simulation and; implementing quality checks on a 4Pi Sun Sensor assembly, including creating an Illumination Test Set-Up. The significance of solar simulators is highlighted, as they are crucial for testing and studying the performance of photovoltaic devices being illuminated by sunlight under various environmental conditions. Different types of solar simulators, such as continuous and pulsed, are explained, along with their uses in calibration, efficiency measurement, material testing, component testing, and research of various devices. The 4Pi Sun Sensor’s role in Attitude Determination is described, emphasising the need for accurate and reliable testing. The methodology employed in both projects is presented. The regular maintenance of the Newport 94043A Solar Simulator and the assembly and testing procedures for the 4Pi Sun Sensor are described in detail. The various tests conducted on the sun sensor, such as visual inspection, electrical tests, illumination tests, and operation of the instruments involved, like the Keithley 2401 Sourcemeter and the Murata SCL3300-D01-PCB tilt sensor, are explained. The results section includes the findings from the solar simulator testing, highlighting the need for replacing the Xe-Arc Lamp and the results from the sun sensor’s illumination tests on different axes. The conclusion emphasises the importance of these projects in understanding solar simulation and sun sensor technology, providing hands-on experience in testing and calibration procedures for photovoltaic devices and spacecraft orientation systems. Overall, these projects contribute to advancement in solar energy and aerospace technology by ensuring accurate testing and calibration of devices used in these fields.

Varying illumination and image blur are some of major challenges faced by contemporary methods of optical flow estimation. Despite significant advancement, these aspects have not received much of attention by modern-day methods. Latest work in this field is heavily affected and produce adverse results when dealing with images containing variable illumination and blur. In this paper, we investigate the effects of color space transformations on optical flow estimation from degraded and noisy images. In our experiments, clean and noisy images have been used. These images contain different kinds of blur and atmospheric effects such as fog, mist, shadows and dark regions. By estimating optical flow with three types of sequences in parallel (super clean, clean and noisy), and using four popular color systems, the effects of color space transformation have been observed on the estimated flow fields. The four color systems include RGB (red, blue, green), HSV (hue, saturation, value), HSL (hue, saturation, lightness) and XYZ (as standardized by the International Commission on Illumination in 1931). It is found that output of an optical flow algorithm not only depends on the color system adopted, but some color spaces tend to favor some special type of image sequences. For instance, XYZ color system is more favorable for the images abiding by the brightness constancy assumption while HSV color space is more suitable for blurry and noisy images. While keeping rest of the parameters unchanged but only transforming the color-space, we estimated the optical flow. Obviously the results of an algorithm applied to clean images for optical flow, would not be consistent with a flow estimated from same images containing noise. The objective is to compare this adversative effect for different color spaces. The flow estimation errors in four color systems have been reported and compared, and the best color-space is pointed out in each case. The paper also discusses the possible factors behind these variable outcomes with an insight into the basic frameworks of traditional methods for optical flow.

Flower color classification and correlation between color space values with pigments in potted multiflora chrysanthemum

Background: Color evaluation is crucial to evaluate a material’s quality. One alternative method for evaluating material’s color is using photographs analysed by software. This research evaluates the use of digital imaging and software (ImageJ and Photoshop) to obtain color differences of tooth sample in-vitro. Method: The sample used is bovine teeth that were given tea-staining and brushing treatment using five tested toothpastes. Sample’s photographs for each toothpaste’s group (n=4) were taken before and after experiment. DLSR Nikon D90 was used with digital CCD censor, macro lens 105mm, manual setting (ISO 200, F-Stop 5, Shutter Speed 1/400) with distance to sample of 25cm. Sample was positioned in foldable mini-studio-box (24.5x24.5x22.5cm) with LED-lighting (6500-7000 color temperature). The photographs were taken in close room at 11.00am. Two software were used to obtain the color value from pre- and post-experimental photographs of the sample at the middle-third of the sample using CIE-Lab (Commision Internacional de l’Eclairage L*a*b) color system. The resulted color difference (ΔE) value of sample from the two-software were compared using independent T-test and evaluate the measurement accuracy using Pearson’s correlation (α=0.05). Result: ImageJ and Photoshop analyses of the sample photographs yield comparable ΔE values, as determined by an independent T-test (p=0.893). The Pearson correlation test reveals a positive correlation (R=0.904) between the two software. Conclusion: The use of digital photography and software to obtain ΔE values are accurate, representative, and recommended when taking into account the controlled procedure of photographing the sample and analysing the sample's color value.

Three colour systems, defined by the International Commission on Illumination (CIE), have been used to parametrise spectra from microspectrophotometry in the visible range for ten replicates of each of forty inks. The parametrised spectra were used to calculate a likelihood ratio (LR) for pairwise comparisons under the propositions implying that any ink from some suspect document came from the same pen, as that from a control document, versus, the converse proposition which implies the ink from the suspect document came from some other pen. Both univariate and bivariate likelihood ratios for each colour system were calculated. Empirical cross-entropy was selected as an appropriate measure of performance for each system. The bivariate combinations of the CIE-xyz colour system achieve the best results as well as a bivariate combination of a and b variables within the CIE-Lab colour system.

Basic color terms used in Mandarin Chinese have been controversial since first discussed by Berlin and Kay in 1969. Previous studies showed much inconsistency on what should be considered as basic color terms in Mandarin Chinese. In the present study, we investigated categories of color rather than merely the color terms used by Taiwanese native Mandarin speakers. Using samples conforming to the Berlin and Kay survey, various colors were chosen from a collection of Natural Color System (NCS) colored papers and mounted on a piece of neutral gray card. The card was then mounted on a touch-screen, under D65 illumination. Thirty-two single-character color related Mandarin terms were selected from a Chinese character database according to frequency of use. Participants were required to select the color sample that matched the term by pressing a virtual button on the touch screen. The results show that certain terms can be directly correlated to basic color terms in English, comparable with the results of Berlin and Kay’s original study and those that followed. However, some terms, such as Mo (墨 ink), Tie (鐵 iron), and Cai (菜vegetable), show a wide spread of term maps and inconsistent use among subjects. Principle component analysis (PCA) procedures were used to analysis the commodity of data among subjects. The findings suggest that the basic color categories among Mandarin Chinese speakers are similar to those found in the World Color Survey (WCS), but are represented by wide-spread and inconsistent color terms among speakers.