An exploration of malayalam basic and nonbasic color terms during a color naming task and in naturalistic narratives

Languages show variations in their basic color terms [Basic Color Terms: Their Universality and Evolution. Berkeley, CA: University of California Press; 1969]. Evidence for languages that have or lack basic color terms mainly comes from standardized naming tasks [The World Color Survey. Stanford, CA: CSLI; 2010]. In this article, we take a somewhat different perspective on the issue of color naming in languages. Starting from a language, Malayalam, with a limited number of basic color terms, and thus with a mixed color naming system, we ask how language users behave when they are asked to produce spontaneous narratives in a communicative setting in which color is manipulated systematically. Do narrators behave as predicted by naming task results and grammars, or do they behave (systematically) differently? In this article, we explore how two different color naming settings affect the expression of colors that have basic color terms in contrast with nonbasic terms. For this purpose, a color naming task was administered to validate basic and nonbasic color terms in Malayalam. The result showed that Malayalam has six colors considered simple color terms (e.g., chuvappu ‘red’) and five complex color terms (e.g., tavittu‐niram brown “color of rice bran”). This result was used to develop eight short stories in two color term conditions. The color terms extracted out from “naturalistic narratives” were more varied than those that were predicted by the color naming task. In the Malayalam primary color condition, respondents often used complex constructions rather than simple color terms only [e.g., chuvappu niram(ulla)]. In the secondary color condition, respondents, as expected, used more complex constructions, but they also avoided complex constructions in interesting ways. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 193–202, 2017     

A cross‐cultural colour‐naming study. Part I: Using an unconstrained method

Colour naming by panels of British and Taiwanese subjects (speaking English and Mandarin, respectively) was used to study colour categorization, and the results applied to investigate differences of usage between the two languages. Fifty British and 40 Chinese subjects took part in experiments using an unconstrained method with 200 ISCC‐NBS colour samples. Data analysis was performed to calculate the frequency and codability of each colour name in each group and subgroup. These names were then grouped using 7‐category and 4‐category methods to find the culture and gender differences. It was confirmed that the 11 basic names found by Berlin and Kay were the most widely used for both languages. The results showed a close agreement between the two languages in terms of colour categories, but a large discrepancy in the use of secondary names due to cultural differences. The cross‐cultural comparison revealed a clear pattern of the linkage between language and concepts of colour. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 40–60, 2001     

A cross‐cultural colour‐naming study: Part II—Using a constrained method

This study aimed to investigate the differences in colour naming between the English (British) and Mandarin (Taiwanese) languages. A constrained method was employed, with 20 British and 20 Chinese adults. All the experiments were conducted under an artificial daylight, using 1526 colours from the Natural Color System (NCS). Each subject was asked to find the colour(s) corresponding to basic names, modifiers, and secondary names in terms of one colour (focal colour) or a colour region (colour volume). Little difference in chromaticness and hue was found between the two languages, but a systematic discrepancy was found in blackness. Because this could have been caused by different surrounds, i.e., gray and white walls used for the British and Chinese experiments, respectively, a verification experiment was carried out using a panel of ten Taiwanese subjects against a gray surround. The results proved that the lightness difference found earlier was indeed caused by the surround. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 193–208, 2001     

A similarity‐based cross‐language comparison of basicness and demarcation of “blue” terms

To investigate linguistic and perceptual boundaries within the “blue” region of the color gamut, we analyzed sorting data from speakers of six languages who sorted color stimuli by similarity. Two of these languages, Russian and Italian, are thought to have a separate basic color term and category for “light blue,” distinguishing it from “blue,” and the third was English, which lacks this distinction. There has been less study of the possible basicness of “light blue” terms in the other three languages: Lithuanian and Estonian (both spoken in Baltic states) and Udmurt (a linguistic enclave in North Russia). Sorting data from each sample of speakers were analyzed with principal component analysis and multidimensional scaling, reducing them to a pattern of interstimulus similarities. In addition, color‐naming data were collected for five of the languages and confirmed that sorting responses were not simply a reflection of the words used by subjects to label the stimuli. A “clustering index” was created, quantifying the extent of light/dark blue separation and the strength of any category boundary between them; this was low for English‐language participants but high for Russian and Italian. Udmurt and Lithuanian values were also high, whereas Estonian responses were closer to English. Thus, when clustering of blue stimuli is used as an additional indicator of basicness, the results are compatible with earlier evidence that “light blue” is a separate basic color category in Russian and Italian, and further indicate that light blue terms are basic in Udmurt and Lithuanian, but not Estonian. It may be that “blue” categories are especially susceptible to splitting into two under the influence of linguistic contact. © 2016 Wiley Periodicals, Inc. Col Res Appl, 42, 362–377, 2017     

An online color naming experiment in Russian using Munsell color samples

Russian color naming was explored in a web‐based experiment. The purpose was 3‐fold: to examine (1) CIELAB coordinates of centroids for 12 Russian basic color terms (BCTs), including 2 Russian terms for “blue”, sinij “dark blue”, and goluboj “light blue”, and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (2) frequent nonBCTs; and (3) gender differences in color naming. Native Russian speakers participated in the experiment using an unconstrained color‐naming method. Each participant named 20 colors, selected from 600 colors densely sampling the Munsell Color Solid. Color names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The 2 “Russian blues”, as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of “brown” and “red”. The Russian color inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of nonBCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of nonBCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of color space, employing a synthetic observer, revealed gender differences in naming colors, with more refined naming of the “warm” colors from females. We conclude that, along with universal perceptual factors, that govern categorical partition of color space, Russian speakers’ color naming reflects language‐specific factors, supporting the weak relativity hypothesis.     

A cross‐cultural colour‐naming study. Part III—A colour‐naming model

A colour‐naming model was developed to categorize volumes for each of the 11 basic names in CIELAB colour space. This was tested with three different sets of data for two languages (English and Mandarin), derived from extensive colour categorization experiments. The performance of the model in predicting colour names was satisfactory, with an average prediction error of 8.3%. © 2001 John Wiley & Sons, Inc. Col Res Appl, 26, 270–277, 2001     

Colour category foci of Munsell colour spectra revealed by two computational methods

Colour names and psychophysical colour categories play an important role on human communication. For several application areas from computer vision to Internet shopping, it would be useful to manage colour information using methods of computational colour naming in a similar manner as people do in their everyday life. In this study, we applied two computational methods, the nonnegative matrix factorization and self‐organizing maps, to derive basic colours from a spectral database of Munsell colours, and a subset of it. The subset was generated to include only the most saturated samples of each Munsell Hue and Munsell Value pair of the original database. Using both the methods and both the databases, we calculated the sets of 3, 4, 6, and 8 basis vectors to represent the focal colours of colour categories. Colour names of the calculated focal colours were investigated using the results by Sturges and Whitfield as a reference. Nonnegative matrix factorization yields calculated colours more compatible with human basic colours, but the spectra generated by self‐organizing maps are more similar to natural spectra as their shape is smoother. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Colour harmony of two‐colour combinations using a 3D colour configuration

Over the past few years, although many studies have investigated colour harmony, most of those used the planar colour configuration, which is not in line with the design requirements of real‐life products. Therefore, this study used 11 basic colours and five types of colour scheme techniques to derive 141 colour combinations applied upon a physical 3D colour configuration to observe the phenomena of colour harmony. The results show that colour harmony on a 3D colour configuration is different from that on a planar colour configuration, and can be divided into four phenomena: (i) lightness difference was found to determine the colour harmony while achromatic colour was configured with achromatic colour; (ii) lightness sum prompted colour harmony while chromatic colour was configured with achromatic colour; (iii) lightness sum and chroma sum were found to determine colour harmony while chromatic colour was configured with chromatic colour with a two‐colour hue angle difference >90°; and (iv) lightness sum and hue difference were a determination of colour harmony while chromatic colour was configured with chromatic colour with a two‐colour hue angle difference of ≤90°. On the basis of these phenomena, this study develops a colour harmony model based on the colour parameters, most of which are derived from the addition of the colour attributes of two colours.     

Augmenting basic colour terms in english

In an unconstrained colour naming experiment conducted over the web, 330 participants named 600 colour samples in English. The 30 most frequent monolexemic colour terms were analyzed with regards to frequency, consensus among genders, response times, consistency of use, denotative volume in the Munsell and OSA colour spaces and inter‐experimental agreement. Each of these measures served for ranking colour term salience; rankings were then combined to give a composite index of basicness. The results support the extension of English inventory from the 11 basic colour terms of Berlin and Kay to 13 terms by the addition of lilac and turquoise. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 32–42, 2016     

Colour-matching Ability—Can it be Measured?

Conventional colour-vision tests can be used for selecting colour workers, and to do this it is necessary to assess the predictive value of the tests in some particular industrial task involving colour. Little research on this topic has so far been carried out, but the results of four such studies are examined, showing that, when the task is simple and entails only the recognition and correct naming of well-known colours, dichromats alone fail to carry it out. For this purpose, the use of tests capable of detecting such colour defects is sufficient and this also applies if the matching of identical colours is involved. However, if it is necessary to measure competence in matching using a visual colorimeter, only the anomaloscope is capable of doing so.     

Colour management of a low‐cost four‐colour ink‐jet printing system on textiles

A low‐cost four‐colour (RBYK) dye‐based ink‐jet printing system for textiles was introduced in this study, in which red and blue inks were employed instead of the magenta and cyan inks used in half‐tone printing. The basis of a colour‐management system for this device was developed by determining the mapping between XYZ tristimulus values of output colours and the digital RBYK values using polynomial transforms. A second‐order equation was found to give the best performance with an average characterisation error of under 7 CIELAB units.     

Properties of ink‐jet printed,ultraviolet‐cured pigment prints in comparison with screen‐printed,thermo‐cured pigment prints

A collection of printed fabrics for men’s shirts was designed and prepared using computer‐aided design/computer‐aided manufacturing technology. The colours for designs were ink‐jet printed on cotton fabrics with pigments and ultraviolet‐cured. These prints represented the target colours for subsequent flat‐screen printing, which was performed using pigment printing pastes and thermal curing. For an exact transfer of colours of the ink‐jet‐printed standard into the screen‐printing process, a computer recipe prediction method was used. A comparison of colorimetric parameters of fabrics printed with both printing techniques shows minimal and acceptable differences in the CIELab colour values. A comparison of colour fastness properties proves that very good colour fastness is achieved on the pigment‐printed fabrics produced with both printing techniques. The flat‐screen‐printed fabrics show better colour fastness to washing, perspiration and rubbing, while ink‐jet‐printed fabrics show better colour fastness to dry‐cleaning and light. The fabrics printed with both printing techniques have high rigidity and non‐elastic properties. The mechanical and physical parameters are strongly dependent upon the amount of the dry substance of the printing media applied on the cotton fabric surface, which is higher on screen‐printed fabrics. The ink‐jet‐printed fabrics show better air permeability than flat‐screen‐printed fabrics.     

Tactile colour pictogram to improve artwork appreciation of people with visual impairments

A recent development in tactile technology enables an improvement in the appreciation of the visual arts for people with visual impairment (PVI). The tactile sense, in conjunction with, or a possibly as an alternative to, the auditory sense, would allow PVIs to approach artwork in a more self‐driven and engaging way that would be difficult to achieve with just an auditory stimulus. Tactile colour pictograms (TCPs), which are raised geometric patterns, are ideographic characters that are designed to enable PVIs to identify colours and interpret information by touch. In this article, three TCPs are introduced to code colours in the Munsell colour system. Each colour pattern consists of a basic cell size of 10 mm × 10 mm to represent the patterns consistently in terms of regular shape. Each TCP consists of basic geometric patterns that are combined to create primary, secondary, and tertiary colour pictograms of shapes indicating colour hue, intensity and lightness. Each TCP represents 29 colours including six hues; they were then further expanded to represent 53 colours. Two of them did not increase the cell size, the other increased the cell size 1.5 times for some colours, such as yellow‐orange, yellow, blue, and blue‐purple. Our proposed TCPs use a slightly larger cell size compared to most tactile patterns currently used to indicate colour, but code for more colours. With user experience and identification tests, conducted with 23 visually impaired adults, the effectiveness of the TCPs suggests that they were helpful for the participants.     

A study of colour emotion and colour preference. Part II: Colour emotions for two‐colour combinations

Eleven colour‐emotion scales, warm–cool, heavy–light, modern–classical, clean–dirty, active–passive, hard–soft, harmonious–disharmonious, tense–relaxed, fresh–stale, masculine–feminine, and like–dislike, were investigated on 190 colour pairs with British and Chinese observers. Experimental results show that gender difference existed in masculine–feminine, whereas no significant cultural difference was found between British and Chinese observers. Three colour‐emotion factors were identified by the method of factor analysis and were labeled “colour activity,” “colour weight,” and “colour heat.” These factors were found similar to those extracted from the single colour emotions developed in Part I. This indicates a coherent framework of colour emotion factors for single colours and two‐colour combinations. An additivity relationship was found between single‐colour and colour‐combination emotions. This relationship predicts colour emotions for a colour pair by averaging the colour emotions of individual colours that generate the pair. However, it cannot be applied to colour preference prediction. By combining the additivity relationship with a single‐colour emotion model, such as those developed in Part I, a colour‐appearance‐based model was established for colour‐combination emotions. With this model one can predict colour emotions for a colour pair if colour‐appearance attributes of the component colours in that pair are known. © 2004 Wiley Periodicals, Inc. Col Res Appl, 29, 292–298, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20024     

An efficient method for solid‐colour and multicolour region segmentation in real yarn‐dyed fabric images

This paper presents an efficient approach to solid‐colour and multicolour region segmentation in real yarn‐dyed fabric images. The approach is based on a novel model describing the spectral response of a multispectral imaging system to yarn‐dyed fabrics. The model indicates that solid‐colour regions cannot be distinguished from multicolour regions in terms of reflectance, tristimulus, or CIELAB values owing to a geometric term representing the influence of fabric surface condition on measured colours. The geometric term makes it difficult to determine the segmentation thresholds of CIEXYZ and CIELAB colour histograms. However, solid‐colour and multicolour regions can be detected in CIExyY space because chromaticity coordinates are impervious to the geometric term. The CIExyY histograms of a solid‐colour region accord with one Gaussian distribution, but those of a multicolour region accord with a combination of two Gaussian distributions. The CIEXYZ, CIELAB, and CIExyY colour distributions of both solid‐colour and multicolour yarn‐dyed fabrics were analysed in detail in simulation and real experiments. Experimental results show that solid‐colour yarn‐dyed regions can be distinguished from multicolour yarn‐dyed fabric regions by the shapes of CIExyY histograms, but cannot be distinguished by the shapes of CIEXYZ or CIELAB histograms.     

Mathematical approach for predicting non‐negative tristimulus values using the CAT02 chromatic adaptation transform

It has been reported that for certain colour samples, the chromatic adaptation transform CAT02 imbedded in the CIECAM02 colour appearance model predicts corresponding colours with negative tristimulus values (TSVs), which can cause problems in certain applications. To overcome this problem, a mathematical approach is proposed for modifying CAT02. This approach combines a non‐negativity constraint for the TSVs of corresponding colours with the minimization of the colour differences between those values for the corresponding colours obtained by visual observations and the TSVs of the corresponding colours predicted by the model, which is a constrained non‐linear optimization problem. By solving the non‐linear optimization problem, a new matrix is found. The performance of the CAT02 transform with various matrices including the original CAT02 matrix, and the new matrix are tested using visual datasets and the optimum colours. Test results show that the CAT02 with the new matrix predicted corresponding colours without negative TSVs for all optimum colours and the colour matching functions of the two CIE standard observers under the test illuminants considered. However, the accuracy with the new matrix for predicting the visual data is approximately 1 CIELAB colour difference unit worse compared with the original CAT02. This indicates that accuracy has to be sacrificed to achieve the non‐negativity constraint for the TSVs of the corresponding colours. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011     

Colour appearance shifts in two different‐sized viewing conditions

This study assessed the effect of size on colour appearance, using a colour matching paradigm where two sizes were presented in a setting similar to a normal colour selection interface. Twelve colours sampling the entire range of the colour spectrum were chosen as target stimuli. The target stimuli consisted of either a large (30° by 50°) or a small (0.5° by 0.5°) test field displayed on a cathode ray tube (CRT). In the experiment, a set of small colour samples consisting of the target and its neighboring colours was presented on the screen. Fifty‐seven participants were asked to pick a colour from the sample set that appeared to exactly match the target. Results in CIECAM02 showed a consistent increase in the apparent brightness (Q) but some decrease in saturation (s) for the larger field. Hue shifts were observed to form a systematic pattern. We noticed a discernable trend showing that, for targets of bluish or purplish colour hues, the accuracy of colour matching is lower and colour difference is greater in the condition of the large viewing field. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Differences in color naming and color salience in Vietnamese and English

The accepted model of color naming postulates that 11 “basic” color terms representing 11 common perceptual experiences show increased processing salience due to a theorized linkage between perception, visual neurophysiology, and cognition. We tested this theory, originally proposed by Berlin and Kay in 1969. Experiment 1 tested salience by comparing unconstrained color naming across two languages, English and Vietnamese. Results were compared with previous research by Berlin and Kay, Boynton and Olson, and colleagues. Experiment 2 validated our stimuli by comparing OSA, Munsell, and newly rendered “basic” exemplars using colorimetry and behavioral measures. Our results show that the relationship between the visual and verbal domains is more complex than current theory acknowledges. An interpoint distance model of color‐naming behavior is proposed as an alternative perspective on color‐naming universality and color‐category structure. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 113–138, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10131     

Optimal yarn colour combination for full‐colour fabric design and mixed‐colour chromaticity coordinates based on CIE chromaticity diagram analysis

It is challenging for textile designers to achieve full‐colour effects in woven fabric using a limited set of coloured yarns. The common problems encountered during full‐colour fabric design include an insufficient number of colours and a failure to match the fabric colour with the desired colour. Using the theories of primary colours and optical colour mixing, we examine the mixed‐colour distribution of primary colour yarns on the basis of the CIE 1976 chromaticity diagram (CIE u′v′). In our experiment, dope‐dyed polyester filament yarns were selected as raw materials. Eight kinds of gradually varied weave structures and four types of primary colour combination were adopted in order to make different types of full‐colour fabric colour chart. Spectrophotometer and DigiEye colour measurement systems were selected to measure the reflectance and colour value of the fabric samples. By comparing the colour distribution of mixed fabrics in the CIE u′v′ diagram, the relationship between the primary colour combinations and the colour distribution of mixed fabrics is discussed. Of RGB, CMY, NCS, and RGBCMY combinations, only RGBCMY resulted in a relatively complete and large colour gamut. Moreover, the colour positions of mixed fabrics in the CIE u′v′ diagram were almost all distributed on or near the connecting line of the primary colour coordinates. The specific colour position of mixed fabrics in the CIE u′v′ diagram were mainly determined by the proportion of primary colours on the fabric surface. In this way, a new method for computing colour position in the CIE u′v′ diagram is introduced.     

A data set for fuzzy colour naming

In computer vision, colour naming has been posed as a fuzzy‐set problem where each colour category is modeled by a function that assigns a membership value to any given sample. However, the success in the automation of this process relies on having an appropriate psychophysical data set for this purpose. In this article we present a data set obtained from a colour‐naming experiment. In this experiment, we used a scoring method to collect a set of judgments adequate for the fuzzy modeling of the colour‐naming task. The data set is composed of 387 colour reflectances, their CIELab and Munsell values, and the corresponding judgments provided by the subjects in the experiment. These judgments are the membership values to the 11 basic colour categories proposed by Berlin and Kay (Berlin B, Kay P. Berkeley: University of California; 1969). All these data have been made available online ( http://www.cvc.uab.es/color_naming ) and, in this article we provide a wide analysis of them. To prove the suitability of the proposed scoring methodology, we have computed a set of common statistics in colour‐naming experiments, such as consensus and consistency, on our data set. The results make it possible for us to conclude the coherence of our data with previous experiments and, thus, its usefulness for the fuzzy modeling of colour naming. © 2005 Wiley Periodicals, Inc. Col Res Appl, 31, 48–56, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20172