Product color emotional design considering color layout

Citations Over TimeTop 11% of 2018 papers

Abstract

Abstract Emotional experience and demand for product colors are important factors in users' decisions to buy and use a product. Therefore, accurately characterizing users' emotional responses of the product's color has become a significant consideration for product color design. However, a product color design problem exists in which it is challenging to accurately and efficiently position users' color image space because consumers have completely different image perceptions when encountering a large number of color schemes generated by different color spatial distributions. For this reason, this article proposes a product color emotional design method that considers the color layout. A table is built of an elemental composition for product color design, which contains color layout forms. This article also establishes a mapping model based on the semantic difference and back propagation neural network between the users' color image perceptions and the elements of the product's color design. The system recommends a color layout form that matches the users' emotional image goal through the k‐nearest neighbor algorithm, and then the form is initialized using a genetic algorithm. The system can realize the solution to the optimal product color scheme by optimizing and evaluating the population. Designers can make intuitive choices and decisions through the product color recommendation system. Through an example of color design for industrial vacuum cleaners, this article shows that the method has satisfactory feasibility and applicability for solving the problem of the optimization of product color design with color layout forms.

Related Papers

• → A Novel Algorithm Based on Improved BP Neural Network and Its Application in Color Management(2013)3 cited
• → On the Uniform Sampling of CIELAB Color Space and the Number of Discernible Colors(2013)2 cited
• → <title>Hybrid color spaces applied to image database</title>(2003)4 cited
• → <title>Digital halftoning based on color correction using neural network with uniform color samples and vector error diffusion</title>(1999)1 cited
• Color quantization of color images in a homogeneous color space(2002)