Coherence of achromatic, primary and basic classes of colour categories

Brightness and hue judgment of dyed hair color

This study aims to investigate human hair color perception through two empirical studies in the context of colored hair. The preliminary study was intended to establish a numerical representation of perceptually meaningful brightness levels. It identified that the brightness level was proportional to the power of 0.766 of L*. In the visual assessment, participants (N = 47) categorized 246 hair color samples into eight color hue groups aligned with the Munsell system. Hue judgment was conducted by visually comparing dyed hair tresses with natural black hair. Based on the L*, a*, and b* values of hair tresses and visual assessments thereof, we observed the ranges of hue categories for hair color alongside the brightness levels. Additionally, the differences between the Munsell hue names and the assessment results were compared. Predominantly influenced by the dark brown hair color, the neutral orientation was shifted to the first quadrant of the a*-b* plane. The study contributes to an understanding of human hair color perception and provides insights into color categorization and labeling, especially when the context is confined.

Color appearance and the end of Hering's Opponent-Colors Theory

Hering's Opponent-Colors Theory has been central to understanding color appearance for 150 years. It aims to explain the phenomenology of colors with two linked propositions. First, a psychological hypothesis stipulates that any color is described necessarily and sufficiently by the extent to which it appears reddish-versus-greenish, bluish-versus-yellowish, and blackish-versus-whitish. Second, a physiological hypothesis stipulates that these perceptual mechanisms are encoded by three innate brain mechanisms. We review the evidence and conclude that neither side of the linking proposition is accurate: the theory is wrong. We sketch out an alternative, Utility-Based Coding, by which the known retinal cone-opponent mechanisms represent optimal encoding of spectral information given competing selective pressure to extract high-acuity spatial information; and phenomenological color categories represent an adaptive, efficient, output of the brain governed by behavioral demands.

ABANICCO: A New Color Space for Multi-Label Pixel Classification and Color Analysis

Classifying pixels according to color, and segmenting the respective areas, are necessary steps in any computer vision task that involves color images. The gap between human color perception, linguistic color terminology, and digital representation are the main challenges for developing methods that properly classify pixels based on color. To address these challenges, we propose a novel method combining geometric analysis, color theory, fuzzy color theory, and multi-label systems for the automatic classification of pixels into 12 conventional color categories, and the subsequent accurate description of each of the detected colors. This method presents a robust, unsupervised, and unbiased strategy for color naming, based on statistics and color theory. The proposed model, "ABANICCO" (AB ANgular Illustrative Classification of COlor), was evaluated through different experiments: its color detection, classification, and naming performance were assessed against the standardized ISCC-NBS color system; its usefulness for image segmentation was tested against state-of-the-art methods. This empirical evaluation provided evidence of ABANICCO's accuracy in color analysis, showing how our proposed model offers a standardized, reliable, and understandable alternative for color naming that is recognizable by both humans and machines. Hence, ABANICCO can serve as a foundation for successfully addressing a myriad of challenges in various areas of computer vision, such as region characterization, histopathology analysis, fire detection, product quality prediction, object description, and hyperspectral imaging.

Basic color categories in Mandarin Chinese revealed by cluster analysis

Previous claims of the number of color categories and corresponding basic color terms in modern Mandarin Chinese remain irreconcilable, mainly due to the shortage in objectively evaluating the basicness of color terms with statistical significance. Therefore the present study applied k-means cluster analysis to investigate native Mandarin Chinese speakers’ color naming data of 330 color chips similar to those used in World Color Survey. Results confirmed that there are 11 basic color categories among modern Mandarin speakers in Taiwan, one corresponding to each basic color term. Results also showed that observers overwhelmingly agreed in their use of Mandarin color terms, including those that had yielded ambiguous results in previous studies (gray, brown, pink, and orange). There is significant cross-language similarity when comparing the distribution of color categories in the World Color Survey chart with American English and Japanese data. The motif analysis and group mutual information analysis suggest that Mandarin color terms used in Taiwan describe very similar categories and are, hence, similarly precise in communicating color information as those in Japanese and American English. These results show that three languages of fundamentally different cultures and histories have very similar basic color terms.