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Creating, Interpreting and Rating Harmonic Colour Palettes Using a Cognitively Inspired Model

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Abstract

This paper presents a cognitively inspired qualitative theory, \(QCharm\), which defines five operators for colour combination based on the qualitative colour descriptor (QCD) and applies these operators to recommend palettes of harmonic colours. Machine learning techniques have been applied to learn the QCD colour coordinates in Kobayashi’s colour space, in order to assign the resulting \(QCharm\) harmonic-colour palettes to cognitive keywords representing a feeling or a lifestyle. Furthermore, a regression model has been implemented to learn users’ preferences based on the COLOURlovers dataset. The resulting model is used as an additional criterion for recommendation. The resulting cognitive system can recommend (i) colour palettes using keywords on feelings/lifestyle, and (ii) colour palettes using the learnt user’s preference model. As an example of the practical applicability of the model, a web application, the \(QCharm\) tool, has been implemented to provide recommendations to users in an interactive way. The \(QCharm\) tool can also extract colour palettes from digital images and assign a cognitive adjective to describe colour combinations, to serve as a starting point for the design process.

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Notes

  1. In this paper, the referred colour is not a figural colour; that is, colours in the observed colour sets are not supposed to play specific roles, e.g. one as a figure and one as a background, as it was done by Palmer and Grissom [44]. Here, all colours have the same significance. [46]

  2. In these cases, there are combinations with some equal colour. For example, if \(k = 0\) and \(a_{1}=a_{2}=a_{3}= 0\), then a unique colour is obtained of colours with different hues and different prefixes, a generalization of the former functions, denoted by \(QCharm_{k,a_{1},a_{2},a_{3}}(h, a)\) is given as:

    $$QCharm_{k,a_{1},a_{2},a_{3}}: H\times A \rightarrow (H\times A)^{3}$$
    $$\begin{array}{l} QCharm_{k,a_{1},a_{2},a_{3}}(h, a)= \\ \{(h-k, a+a_{1}), (h,a+a_{2}), (h +k, a+a_{3}\}(\bmod N, \bmod 4) \end{array}$$

    where \(h\in H\), \(a\in A\), \(k\in \{0, 1,2,round(N/2)\}\) and \(a_{i}\in \{0, 1, 2, 3\}\) for \(i = 1,2,3\).

  3. http://www.colorlovers.com/

  4. http://bscc.spatial-cognition.de/

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Funding

Dr. Museros, Dr. Sanz and Prof. Dr. Gonzalez-Abril acknowledge the funding by the Spanish Ministry of Economy and Competitiveness (TIN2017-88805-R) and Universitat Jaume I (UJI-B2017-73).

Dr.-Ing. Falomir acknowledges the funding and support by the Bremen Spatial Cognition CenterFootnote 4 (BSCC), and the University Bremen under project Cognitive Qualitative Descriptions and Applications (CogQDA).

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Authors and Affiliations

  1. Engineering and Computer Science Department, Universitat Jaume I, Av. Vicent Sos Baynat s/n, 12071, Castellón, Spain

    Lledó Museros & Ismael Sanz

  2. Bremen Spatial Cognition Center, University of Bremen, Enrique-Schmidt-Str. 5, 28359, Bremen, Germany

    Zoe Falomir

  3. Economia Aplicada I Department, Universidad de Sevilla, Avda Ramon y Cajal, 1, 41018, Sevilla, Spain

    Luis Gonzalez-Abril

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  1. Lledó Museros
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Correspondence to Lledó Museros.

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Museros, L., Sanz, I., Falomir, Z. et al. Creating, Interpreting and Rating Harmonic Colour Palettes Using a Cognitively Inspired Model. Cogn Comput 12, 442–459 (2020). https://doi.org/10.1007/s12559-018-9589-2

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