PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
September 18, 2025Crystals3 citationsOpen Access

Colorimetric Properties and Classification of “Tang yu”

View Full Paper
KLKaichao LiuJTJun TangYGYing Guo

Key Points

  • D65 light source maintains color balance, enhancing the color grading of Tang Yu samples.
  • Glassy polishing method significantly raised Lightness by 11.41% and Chroma by 42.11%, shifting hues to red-yellow.
  • Background luminance critically increases Lightness and Chroma, affecting color perception though Hue angle remains stable.
  • Cluster and discriminant analyses classified Tang Yu colors into three groups, laying groundwork for a grading system.

Abstract

This study quantitatively analyses how light sources, polishing methods, and backgrounds affect the color of “Tang yu”. Twenty-four samples were tested with three different light sources (D50, A, D65), two polishing methods, and nine Munsell neutral gray backgrounds. Testing 24 samples revealed that main coloring elements exhibit low concentrations with no linear relationship to color intensity. Light sources selectively alter chromaticity: D65 maintains color balance (recommended for grading), while A enhances red tones. Polishing methods significantly impact color perception, with glassy polishing markedly increasing Lightness (L*↑11.41%) and Chroma (C*↑42.11%) while shifting hues toward red-yellow. Background luminance (γb) critically influences color results: Lightness L* and Chroma C* increase via distinct power functions as γb rises, though Hue angle (h°) remains stable. Sample color can be predicted through γb based equations, with Munsell N9 background proving optimal for grading. Cluster and discriminant analyses effectively classified colors into three distinct groups, establishing a foundation for a reliable grading system.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/68d463f131b076d99fa6360ahttps://doi.org/10.3390/cryst15090817
Ask AI
Helpful
Bookmark
Share
View Full Paper