Abstract
In an early study, the so-called “relevant colour” in a painting was heuristically introduced as a term to describe the number of colours that would stand out for an observer when just glancing at a painting. The purpose of this study is to analyse how observers determine the relevant colours by describing observers’ subjective impressions of the most representative colours in paintings and to provide a psychophysical backing for a related computational model we proposed in a previous work. This subjective impression is elicited by an efficient and optimal processing of the most representative colour instances in painting images. Our results suggest an average number of 21 subjective colours. This number is in close agreement with the computational number of relevant colours previously obtained and allows a reliable segmentation of colour images using a small number of colours without introducing any colour categorization. In addition, our results are in good agreement with the directions of colour preferences derived from an independent component analysis. We show that independent component analysis of the painting images yields directions of colour preference aligned with the relevant colours of these images. Following on from this analysis, the results suggest that hue colour components are efficiently distributed throughout a discrete number of directions and could be relevant instances to a priori describe the most representative colours that make up the colour palette of paintings.
Highlights
The colourimetric analysis of pictorial works has aroused much interest in recent years, because of the study of the style used by the painter and because of the computational applications that can be derived from the analysis of the statistical properties that characterize their spatial–chromatic content [1,2,3,4,5,6,7] and, the study of where a subject fixates their gaze when they observe works of art
Similar results were obtained for all observers, which means that the observers were able to subjectively select a reduced number of colours that were representative of the remarkable colours describing the painting
The results we found in this experiment illustrate how observers are able to pick the most relevant colours that describe the subjective impression gained by the observation of paintings
Summary
The colourimetric analysis of pictorial works has aroused much interest in recent years, because of the study of the style used by the painter and because of the computational applications that can be derived from the analysis of the statistical properties that characterize their spatial–chromatic content [1,2,3,4,5,6,7] and, the study of where a subject fixates their gaze when they observe works of art. There are several studies [8] that prove how eye fixations allow observers to perceive scene content and concentrate on local (i.e., lines, segments, shapes, or focus regions) and global (i.e., figure and ground, colour gamut, or edge distribution) features. Most of these approaches usually work with a fixed number of colours as a result of applying clustering and/or learning-based approaches
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