Color Design Decisions for Ceramic Products Based on Quantification of Perceptual Characteristics

Author:

Wang Yi,Zhao Qinxin,Chen Jian,Wang Weiwei,Yu Suihuai,Yang Xiaoyan

Abstract

The appearance characteristics of ceramic color are an important factor in determining the user’s aesthetic perception of the product. Given the problem that ceramic color varies and the user’s visual sensory evaluation of color is highly subjective and uncertain, a method of quantifying ceramic color characteristics based on the Back Propagation (BP) neural network algorithm is proposed. The semantic difference method and statistical method were used to obtain quantified data from ceramic color perceptual semantic features and were combined with a neural network to study the association between ceramic color features and user perceptual-cognitive evaluation. A BP neural network was used to build a ceramic color perceptual semantic mapping model, using color semantic quantified values as the input layer, color L, A, and B component values as the output layer, and model training to predict the sample. The output color L, A, and B components are used as the input layer and the color scheme was designed. The above method can effectively solve the mapping problem between the appearance characteristics of ceramic color and perceptual semantics and provide a decision basis for ceramic product color design. The case application of color design of daily-use ceramic products was conducted to verify the effectiveness and feasibility of the quantitative research method of ceramic color imagery.

Funder

Innovation Capability Support Program of Shaanxi

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference35 articles.

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