Next Article in Journal
Multi-Objective Ship Route Optimisation Using Estimation of Distribution Algorithm
Previous Article in Journal
Mixed-Dimensional Heterostructure Photodetector Based on Bi2O2Se Nanosheets and PbS Quantum Dots
Previous Article in Special Issue
A Novel Line-Scan Algorithm for Unsynchronised Dynamic Measurements
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A Study on the Color Prediction of Ancient Chinese Architecture Paintings Based on a Digital Color Camera and the Color Design System

1
Beijing International Leading Commercial Color Research Center, Beijing 102308, China
2
State Key Discipline Laboratory of Color Science and Engineering, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(13), 5916; https://doi.org/10.3390/app14135916 (registering DOI)
Submission received: 22 April 2024 / Revised: 30 June 2024 / Accepted: 4 July 2024 / Published: 6 July 2024

Abstract

Color paintings such as painted facades and interiors are important decoration elements of ancient Chinese architectures. The color of the paintings usually fades over time due to exposure to strong light, high humidity, high temperatures, and other environmental factors. In order to restore or reproduce the color appearance of ancient architecture paintings correctly, it was necessary to study the color degradation process of such paintings. To meet the needs of on-site colorimetric measurement of the paintings on ancient Chinese architectures, we propose using a digital color camera and the CDS (Color Design System) to measure and evaluate the colors of such paintings. The CDS is a color order system recommended by the Chinese national technical committee for color standardization (SAC/TC 120) in 2017 (GB/Z 35473-2017). The current version of the CDS atlas contains about 2740 samples which were uniformly distributed on the whole color space, and can be used to set up the colorimetric characterization model for the digital camera. Particularly, the digital CDS lookup table contains over 400 thousand samples, and it can be used to express the color of paintings on ancient Chinese architectures. In the experiment, a digital color camera was used to capture the colors of the paintings on the ancient Chinese architectures of different years based on the CDS and polynomial transform method. Moreover, a linear interpolation method was proposed for calculating and predicting the color degradation of such paintings. The experimental results show that with the increase in years, the color hue of the paintings changes slowly, while the lightness and the chroma of them fade obviously. In the future, more ancient architectures of different years and from different places should be selected as experimental samples to improve the method and the results of the paper.
Keywords: ancient architecture color; colorimetric characterization; digital color camera; color degradation of paintings; CDS ancient architecture color; colorimetric characterization; digital color camera; color degradation of paintings; CDS

Share and Cite

MDPI and ACS Style

Lv, G.; Liao, N.; Yuan, C.; Wei, L.; Feng, Y. A Study on the Color Prediction of Ancient Chinese Architecture Paintings Based on a Digital Color Camera and the Color Design System. Appl. Sci. 2024, 14, 5916. https://doi.org/10.3390/app14135916

AMA Style

Lv G, Liao N, Yuan C, Wei L, Feng Y. A Study on the Color Prediction of Ancient Chinese Architecture Paintings Based on a Digital Color Camera and the Color Design System. Applied Sciences. 2024; 14(13):5916. https://doi.org/10.3390/app14135916

Chicago/Turabian Style

Lv, Guang, Ningfang Liao, Chang Yuan, Lizhong Wei, and Yunpeng Feng. 2024. "A Study on the Color Prediction of Ancient Chinese Architecture Paintings Based on a Digital Color Camera and the Color Design System" Applied Sciences 14, no. 13: 5916. https://doi.org/10.3390/app14135916

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop