3D Digital Microscopy Calibration Using Shadows and Color Checks
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Solution Overview
Problem
Existing technologies face challenges in accurately calibrating digital microscopy systems for capturing high-quality digital images of three-dimensional objects, such as rock cuttings and cavings, which are crucial for effective analysis in hydrocarbon reservoir exploration and production operations.
Innovation Solution
A method and system utilizing a digital microscopy system that includes a digital camera, a light source, and a processor to calibrate the system by acquiring images of engineered three-dimensional objects and color checker cards, determining a light source criterion based on shadows and color saturation, to generate a calibrated digital microscopy system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used for digital microscopy systems, then the calibration process is simple, but the accuracy and reliability of digital image acquisition is insufficient
Solution Approach 1:
The system performs preliminary calibration actions by capturing images of calibration objects with known geometric features and color characteristics before actual measurement. The light source position is adjusted in advance to optimize shadow patterns and color saturation, ensuring accurate calibration data is obtained prior to rock sample analysis.
Solution Approach 2:
Calibration objects serve as intermediaries between the light source and the final measurement target. These objects with known properties mediate the calibration process by providing reference patterns for geometric distortion correction and color accuracy verification, enabling the system to achieve high measurement precision without directly measuring the target during calibration.
2Illumination intensity
If light source position is not optimized, then the calibration process is fast, but the color saturation and shadow quality in images are insufficient
Solution Approach 1:
The system uses feedback mechanisms to evaluate the quality of shadows and color saturation in captured calibration images. The processor analyzes the calibration data and provides feedback on light source position quality, allowing iterative optimization of illumination conditions to achieve optimal color saturation and shadow definition for accurate rock property characterization.
Solution Approach 2:
The light source position is made dynamic and adjustable during the calibration process. The system can move the light source to different positions and angles to optimize shadow patterns and color rendering, adapting the illumination conditions to achieve the best image quality for the specific calibration objects and measurement requirements.
3Reliability
If calibration is not performed, then the system operation is simple, but the reliability of rock property characterization is poor
Solution Approach 1:
The calibration process is segmented into distinct components: geometric calibration using objects with known dimensions, color calibration using objects with known color properties, and light source position optimization. This segmentation allows each aspect of calibration to be performed independently and systematically, improving reliability without overwhelming system complexity.
Solution Approach 2:
The system changes multiple parameters during calibration including light source position, illumination intensity, and camera settings. By systematically adjusting these parameters and recording their effects on image quality, the system establishes optimized parameter sets that enhance the reliability of rock property characterization while maintaining manageable operational complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and reliability of digital image acquisition, enabling better characterization of rock properties and improving operational decisions in hydrocarbon reservoir exploration and production.
Implementation Method 1
determining a light source criterion by assessing position of the light source based at least in part on a shadow in the digital image of the engineered three-dimensional object as cast by the engineered three-dimensional object
Implementation Method 2
using a digital camera, acquiring a digital image of an engineered three-dimensional object positioned on a base and illuminated by the light source
Data Source
AI summary
A method can include using a digital camera of a digital microscopy system, acquiring a digital image of an engineered three-dimensional object positioned on a base and illuminated by a light source; using the digital camera, acquiring a digital image of a color checker card positioned on the base and illuminated by the light source; determining a light source criterion by assessing position of the light source based at least in part on a shadow in the digital image of the engineered three-dimensional object as cast by the engineered three-dimensional object and based at least in part on saturation of color in the digital image of the color checker card; and calibrating the digital microscopy system using the light source criterion to generate a calibrated digital microscopy system.