Quantitative microstructural characterization of transparent YAG ceramics via microscopic image analysis using stereological relations

2015 ◽  
Author(s):  
Tereza Uhlířová ◽  
Jan Hostaša ◽  
Willi Pabst ◽  
Laura Esposito
Keyword(s):  
Image Analysis ◽  
Microstructural Characterization ◽  
Microscopic Image ◽  
Microscopic Image Analysis

Color Reproduction Accuracy Promotion of 3D-Printed Surfaces Based on Microscopic Image Analysis

2019 ◽  
Vol 34 (01) ◽  
pp. 2054004 ◽  
Author(s):  
Xiaochun Wang ◽  
Chen Chen ◽  
Jiangping Yuan ◽  
Guangxue Chen
Keyword(s):  
Surface Roughness ◽  
Image Analysis ◽  
Three Dimensional ◽  
Prediction Method ◽  
Chromatic Aberration ◽  
Optimization Methods ◽  
Experimental Models ◽  
Microscopic Image ◽  
Color Reproduction ◽  
Microscopic Image Analysis

Full-color three-dimensional (3D) printing technology is a powerful process to manufacture intelligent customized colorful objects with improved surface qualities; however, poor surface color optimization methods are the main impeding factors for its commercialization. As such, the paper explored the correlation between microstructure and color reproduction, then an assessment and prediction method of color optimization based on microscopic image analysis was proposed. The experimental models were divided into 24-color plates and 4-color cubes printed by ProJet 860 3D printer, then impregnated according to preset parameters, at last measured by a spectrophotometer and observed using both a digital microscope and a scanning electron microscope. The results revealed that the samples manifested higher saturation and smaller chromatic aberration ([Formula: see text]) after postprocessing. Moreover, the brightness of the same color surface increased with the increasing soaked surface roughness. Further, reduction in surface roughness, impregnation into surface pores, and enhancement of coating transparency effectively improved the accuracy of color reproduction, which could be verified by the measured values. Finally, the chromatic aberration caused by positioning errors on different faces of the samples was optimized, and the value of [Formula: see text] for a black cube was reduced from 8.12 to 0.82, which is undetectable to human eyes.

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