Diamond Color Grading via Neural Network and Optical Imaging
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Solution Overview
Problem
The existing methods for grading the color of diamonds are prone to inconsistencies and human error, affecting the reliability and repeatability of the assessment, which can impact the value of the diamond.
Innovation Solution
A computerized system using a pre-trained neural network and optical image acquisition device to determine the color grade of diamonds, with image pre-processing and flat-field correction to ensure consistency and accuracy, and a color domain processing system to provide a reliable color grading.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human graders are used to assess diamond color using standardized color scales, then the assessment can be performed with established industry standards, but the reliability and repeatability are prone to inconsistencies due to human error
Solution Approach 1:
The patent replaces the human visual assessment system with an automated optical imaging and machine learning system. The neural network processes images of diamonds to determine color grades, eliminating human subjectivity and inconsistency while maintaining adherence to industry standards through trained models on reference datasets.
Solution Approach 2:
The system creates digital copies (images) of diamonds for assessment rather than relying on direct human observation. Multiple images are captured under controlled lighting conditions and processed through the neural network, allowing repeated analysis without the variability inherent in human grading.
2Ease of operation
If extensive training is provided to color graders to ensure uniformity and consistency, then different graders can reproduce the same assessment results, but the process remains time-consuming and still prone to inconsistencies
Solution Approach 1:
The system performs self-assessment through automated image capture and neural network processing. The diamond is imaged under controlled conditions and the system automatically determines the color grade without requiring human intervention or training, eliminating the time investment needed for grader education and certification.
Solution Approach 2:
The neural network is pre-trained on extensive datasets of reference diamonds with known color grades before deployment. This preliminary training phase establishes the assessment criteria and enables rapid, consistent grading of subsequent diamonds without requiring real-time human judgment or adjustment.
3Measurement precision
If controlled environment with standardized light box and white tile is used for color grading, then the color of diamond can be graded by referring to master stone, but environmental factors can still affect the assessment
Solution Approach 1:
The system changes the lighting parameters from standardized but variable manual lighting to controlled LED illumination with specific color temperature (5500K±50K). The optical system includes filters and calibrated light sources that maintain consistent spectral characteristics, reducing the impact of environmental variability on color assessment.
Solution Approach 2:
The patent creates a controlled optical environment that isolates the diamond from external environmental influences. The imaging system uses a dark background, controlled illumination, and standardized camera settings to create an inert assessment environment that eliminates external light contamination and atmospheric interference.
Data Source
AI summary
A process is operable using a computerized system for grading the colour of a diamond using a pre-trained neural network for determination of a colour grading. The computerized system includes an optical image acquisition device, a pre-trained neural network and an output module operably interconnected together via a communication link. The process includes: (i) acquiring via an optical image acquisition device one or more optical image of at least a portion of a diamond; and (ii) in a pre-trained neural network, providing a regressive value associated with the colour grade of the diamond.