COLIBRI Fuzzy Model: Color Linguistic-Based Representation and Interpretation
Shamoi P. Toganas N. Muratbekova M. Kadyrgali E. Yerkin A. Igali A. Ziyada M. Adilova A. Karatayev A. Torekhan Y.
2025Institute of Electrical and Electronics Engineers Inc.
IEEE Access
2025#13205932 - 205956 pp.
Colors are omnipresent in today’s world and play a vital role in how humans perceive and interact with their surroundings. However, it is challenging for computers to imitate human color perception. This paper introduces the Human Perception-Based Fuzzy Color Model, COLIBRI (Color Linguistic-Based Representation and Interpretation), designed to bridge the gap between computational color representations and human visual perception. Using a three-phase experimental approach, the study first identifies distinguishable color stimuli for hue, saturation, and intensity through preliminary experiments, followed by a large-scale human categorization survey involving more than 1000 human subjects. The resulting data are used to extract fuzzy partitions and generate membership functions that reflect real-world perceptual uncertainty. To the best of our knowledge, no previous research has documented the construction of a model for color attribute specification based on a sample of this size or a comparable sample of the human population (n=2496). The results show that colors such as green and blue have wide fuzzy sets, indicating broad perceptual tolerance, while yellow, cyan, and light blue form narrow, sharply defined categories. Most hue stimuli achieved >95% agreement, with boundary colors showing moderate ambiguity. Fleiss’ Kappa scores (0.76 hue, 0.56 saturation, 0.49 intensity) confirm strong reliability and consistency across surveys. To demonstrate practical value, we applied COLIBRI to labeling 5,577 product images from the VISUELLE dataset, producing perceptually meaningful dominant-color annotations. Our findings are significant for fields such as design, artificial intelligence, marketing, and human-computer interaction, where perceptually relevant color representation is critical.
color categorization , color perception , fuzzy color model , Fuzzy sets , HSI color model , image processing , linguistic color representation
Text of the article Перейти на текст статьи
Kazakh-British Technical University, School of Information Technology and Engineering, Almaty, 050000, Kazakhstan
Kazakh-British Technical University
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026