GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials

Junhua Zhang; Yulin Zhu

doi:10.47297/taposatWSP2633-456919.20250610

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GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials

6卷第10期

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GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials
GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials
1.Tsung-Dao Lee Institute, Shanghai Jiao Tong University, Shanghai, 201210, China
2.Department of High School, Shanghai Starriver Bilingual School, Shanghai, 201108, China
2025年6卷第10期页码：96-99
纸质出版：2025-10-30
DOI：10.47297/taposatWSP2633-456919.20250610
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Junhua Zhang & Yulin Zhu. (2025). GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials. 科技理论与实践（英文版）, 6(10), 96-99.

Zhang Junhua,Zhu Yulin.GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials[J].Theory and Practice of Science and Technology,2025,06(10):96-99.
Junhua Zhang & Yulin Zhu. (2025). GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials. 科技理论与实践（英文版）, 6(10), 96-99. DOI： 10.47297/taposatWSP2633-456919.20250610.

Zhang Junhua,Zhu Yulin.GLCM-Based Correlation Analysis of Surface Topography and Perceived Color in Decorative Materials[J].Theory and Practice of Science and Technology,2025,06(10):96-99. DOI： 10.47297/taposatWSP2633-456919.20250610.

摘要

Abstract

This study how PP surface topography shapes color appearance. Light-blue and dark-blue samples were polished with SiC papers of varied grits to tune roughness. Optical micrographs were processed to compute GLCM features—ASM

contrast

sum average

sum variance

correlation

and entropy—describing microtexture. CIELAB L*

b* values were measured and linked to texture. Spearman correlations show higher ASM and lower entropy—smoother morphology—associate with higher L* and greener–yellower hues. Canonical correlation analysis reveals a strong multivariate coupling (first r>0.94): entropy dominates the texture side

while a* and b* comparably dominate the color side. It lays a foundation for corresponding machine-learning inspection..

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references

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