Color Scheme Search: A Statistics-Based IEC Method

Ken Ishibashi
Japan Advanced Institute of Science and Technology / Japan Society for the Promotion of Science, Japan

Kazunori Miyata
Japan Advanced Institute of Science and Technology, Japan

Ladda ner artikel

Ingår i: KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13

Linköping Electronic Conference Proceedings 100:76, s. 907-919

Visa mer +

Publicerad: 2014-06-11

ISBN: 978-91-7519-276-5

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


This paper presents a statistics-based interactive evolutionary computation (IEC) method for color scheme search. Color schemes are utilized in an enormous range of items such as websites; clothing; advertising media; and housewares. However; people who do not have sufficient skill or knowledge of colors need to devote considerable time and effort to a creating color scheme. Currently; artists’ color schemes are freely available from websites. However; obtaining an appropriate color scheme from a large data set is difficult for novice users. To overcome this problem; we rely on a statistics-based interactive genetic algorithm (IGA). Use of this IGA is expected to reduce computing costs compared with conventional IEC approaches and to take overall color scheme impressions into account. These contributions enable to realization of the kansei-based color search system in real time. In addition; we introduce four similarity search (SS) functions (hue; saturation; brightness; and color differences) to facilitate the convergence of a color scheme search. The combination of a statistics-based IGA and four SS functions allows users to easily and effectively find their desired color schemes. To investigate the performance of the proposed method; we conducted two experiments and confirmed that the implemented application allows users to obtain a desired color scheme in less than 48 s. In addition; we also confirmed that the proposed method can provide some favorable recolored illustrations in less than 52 s.


Color Scheme Search; Interactive Evolutionary Computation; Statistics; Color Transfer


Chijiiwa; H. (1999). Encyclopedia on color cognition of the world’s youth [in Japanese]; Tokyo: Kawade Shobo Shinsha.

Cohen-Or; D.; Sorkine; O.; Gal; R.; Leyvand; T.; & Xu; Y.-Q. (2006). Color harmonization. ACM Trans. Graph.; 25(3); 624-630.

Cox; J. M. & Davison; A. (2005). The visual analogue scale as a tool for self reporting of subjective phenomena in the medical radiation. The Radiographer; 52; 22-24.

Hsiao; S.-W.; Hsu; C.-F.; & Tang; K.-W. (2013). A consultation and simulation system for product color planning based on interactive genetic algorithms. Color Research & Application; 38; 375-390.

Inoue; H.; Yuan; D.; & Iwatani; K. (2009). Color combination support systems using interactive evolutionary computation [in Japanese]. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics; 21(5); 757-767.

Ito; F.; Hiroyasu; T.; Miki; M.; & Yokouchi; H. (2009). Offspring generation method for interactive genetic algorithm considering multimodal preference [in Japanese]. Transactions of the Japanese Society for Artificial Intelligence; 24(1); 127-135.

Kimura; T.; Ohki; H.; Ueda; K.; Fujiki; Y.; & Sueda; N. (2008). An parameter search method in image processing system based on candidate image selection by user [in Japanese]. Information Processing Society of Japan (IPSJ) Journal; 290(22); 2319–2323.

Kinoshita; Y.; Sakakura; Y.; Cooper; E. W.; Hoshino; Y.; & Kamei; K. (2006). Townscape color planning system using an evolutionary algorithm and kansei evaluations. Proceedings of 2006 IEEE International Conference on Fuzzy Systems (pp. 931-938). Vancouver; BC; Canada.

Kobayashi; S. (1992). Color Image Scale. New York; N: Kodansha USA.

Kobayashi; S. (1995). Art of color combinations (in Japanease). Tokyo: Kodansha.

Kondo; K.; Takahashi; M.; Matsunaga; M.; & Yamazaki; H. (2000). A kansei method for retrieving images from a database using colors [in Japanese]. The Journal of the Institute of Image Information and Television Engineers; 54(11); 1615-1622.

Lin; S.; Ritchie; D.; Fisher; M.; & Hanrahan; P. (2013). Probabilistic color-by-numbers: suggesting pattern colorizations using factor graphs. ACM Trans. Graph.; 32(4); 37:1-37:12.

Lübbe; E. (2010). Colours in the Mind - Colour Systems in Reality (C. Studt; Trans). Norderstedt: BoD.

Matsuda; Y. (1995). Color Design [in Japanese]. Tokyo: Asakura Syoten.

Miki; M.; Okada; N.; Hiroyasu; T.; & Yoshimi; M. (2011). Office space design system using an interactive genetic algorithm [in Japanese] (The science and engineering review; 52(3); 241-222). Doshisha University.

Moon; P. & Spencer; D. E. (1944a). Aesthetic measure applied to color harmony. Journal of the Optical Society of America; 34(4); 234–242.

Moon; P. & Spencer; D. E. (1944b). Area in color harmony. Journal of the Optical Society of America; 34(2); 93–103.

Moon; P. & Spencer; D. E. (1944c). Geometric formulation of classical color harmony. Journal of the Optical Society of America; 34(1); 46–50.

O’Donovan; P.; Agarwala; A.; & Hertzmann; A. (2011). Color compatibility from large datasets. ACM Trans. Graph.; 30(4); 63:1–63:12.

Ou; L.-C.; Luo; M. R.; Woodcock; A.; & Wright; A. (2004). A study of colour emotion and colour preference. part i: Colour emotions for single colours. Color Research & Application; 29(3); 232–240.

Sugahara; M.; Miki; M.; & Hiroyasu; T. (2008). Design of japanese kimono using interactive genetic algorithm. Proceedings of 2008 IEEE International Conference on Systems; Man; and Cybernetics (pp. 185-190). Singapore.

Tobitani; K.; Kato; K.; & Yamamoto; K. (2012). Research of color combination support based on individual kansei using interactive evolutionary computation [in Japanese] (The papers of technical meeting; 2012(1); 49-54). The Institute of Electrical Engineers of Japan.

Troiano; L.; Birtolo; C.; & Chirillo; G. (2009). Interactive genetic algorithm for choosing suitable colors in user interface. Proceedings of Learning and Intelligent OptimizatioN LION3 (pp. 14-18). Trento; Italy

Citeringar i Crossref