Open AccessPreliminary Study on Sapphire Color Grading Method Based on Automatic Clustering Algorithm of Color Space Features
Author(s) -
Liujun Lin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2074/1/012065
Subject(s) - color space , sapphire , artificial intelligence , cluster analysis , computer science , grading (engineering) , pattern recognition (psychology) , euclidean distance , color model , hsl and hsv , computer vision , mathematics , optics , physics , engineering , laser , virus , civil engineering , virology , image (mathematics) , biology
Traditionally, the color grading of sapphire is mainly based on the naked eye judgment of the appraiser. This judgment standard is not clear enough, and the judgment result has a greater subjective influence, which affects the accuracy of the classification. In this study, the GEM-3000 ultraviolet-visible spectrophotometer was selected, and the color features of 180 sapphire samples were extracted and classified using the CIE1976 color space of the device. The Kmeans algorithm was used to cluster analysis of 140 samples, and the separability of the color space features of different color levels was verified, and the center sample of each color level was obtained. The Euclidean distance between the centers of the remaining 40 samples is calculated, and each color grade prediction label is determined, and the sapphire color is automatically classified based on this. The experimental results show that the accuracy of sapphire color classification using the above method is 97.5%, which confirms the effect and accuracy of the artificial intelligence method in sapphire color classification.