Paper Info
Title
Color Design Decisions for Ceramic Products Based on Quantification of Perceptual Characteristics
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.
Year
DOI
Venue
2022
10.3390/s22145415
SENSORS
Keywords
DocType
Volume
industrial design, perceptual semantics, ceramic color, feature quantification, neural network
Journal
22
Issue
ISSN
Citations 
14
1424-8220
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Yi Wang100.34
Qinxin Zhao200.34
Jian Chen32315.42
Weiwei Wang400.34
Suihuai Yu5259.68
Xiaoyan Yang600.68