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Optimizing Parametric Factors in CIELAB and CIEDE2000 Color-Difference Formulas for 3D-Printed Spherical Objects.

Ruili He¹, Kaida Xiao¹, Michael Pointer¹

¹School of Design, Faculty of Arts, Humanities and Cultures, University of Leeds, Leeds LS2 9JT, UK.

Materials (Basel, Switzerland)

|June 24, 2022

Summary

This summary is machine-generated.

Optimizing color-difference formulas for 3D objects is crucial. This study refined CIELAB and CIEDE2000 formulas using 3D printed samples, significantly improving accuracy for 3D color evaluation.

Keywords:

3D object CIEDE2000 CIELAB color difference optimization visual assessment

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Area of Science:

Color Science
Metrology
3D Printing Technology

Background:

Current color-difference formulas are primarily based on 2D samples.
There is a lack of standardized guidance for evaluating color differences in 3D objects.
Accurate color difference assessment is vital in manufacturing and quality control.

Purpose of the Study:

To test and optimize the CIELAB and CIEDE2000 color-difference formulas for 3D-printed spherical samples.
To establish optimized parametric factors for enhanced formula performance.
To validate the improved formulas using independent visual data.

Main Methods:

Utilized 82 pairs of 3D-printed spherical samples for visual assessment.
Conducted experiments with 15 human observers under simulated D65 illumination.
Employed the gray-scale method for visual data collection and analyzed using STRESS index and F-test.
Optimized CIELAB and CIEDE2000 formulas using data from 42 sample pairs (Experiment I).

Main Results:

Identified optimal parametric factors: kL=1.4, kC=1.9 for CIELAB and kL=1.5 for CIEDE2000.
Optimized formulas reduced STRESS values from 32.8/32.9 to 25.3/25.4 for CIELAB/CIEDE2000, respectively.
F-test confirmed a significant improvement in formula performance after optimization.

Conclusions:

The optimized CIELAB and CIEDE2000 formulas demonstrate superior performance for 3D-printed spherical samples.
Parametric adjustments are effective in adapting existing color-difference formulas for 3D applications.
This research provides a foundation for standardized 3D color difference evaluation.