Image Analysis Using Thermal and Visible Defect Correlation
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Solution Overview
Problem
Infrared inspection methods for detecting defective portions in structures, such as bulging or cracked areas, often result in erroneous detections due to factors like thermal conductivity differences, emissivity variations, and surface irregularities, leading to incorrect identification of abnormal portions.
Innovation Solution
An image analysis apparatus and method that combines infrared thermal imaging with visible light imaging to identify temperature defects and surface defects, analyzing their relationship to determine the cause of temperature anomalies, thereby reducing erroneous detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If infrared thermal imaging is used to detect temperature defects, then structural defects such as bulging or cracks can be identified, but erroneous detections occur due to surface irregularities and material property differences
Solution Approach 1:
The patent combines infrared thermal imaging with visible light imaging to create a comprehensive analysis system. The infrared image captures temperature distribution to detect thermal defects, while the visible light image captures surface characteristics. By merging these two imaging modalities, the system can distinguish between actual structural defects and surface irregularities, thereby reducing false positives while maintaining detection accuracy.
Solution Approach 2:
The patent introduces a correlation analysis mechanism as an intermediary between the infrared and visible light images. This intermediary process compares the temperature defect locations from infrared imaging with surface defect locations from visible light imaging to determine causal relationships. The correlation analysis acts as a mediator that filters out false detections by verifying whether temperature anomalies correspond to actual structural issues rather than surface conditions.
2Productivity
If only infrared thermal images are analyzed, then temperature defects can be detected, but surface defects like color unevenness and foreign substances cause erroneous detections
Solution Approach 1:
The patent adds another dimension to the detection process by incorporating visible light imaging alongside infrared thermal imaging. The visible light image provides information about surface characteristics such as color unevenness, foreign substances, and surface defects. By analyzing both thermal and visible dimensions simultaneously, the system maintains high detection speed while significantly improving detection accuracy through multi-dimensional correlation analysis.
3Reliability
If multivariate analysis is applied to determine fault probability, then detection reliability improves, but the complexity of the analysis system increases
Solution Approach 1:
The patent performs preliminary actions by automatically extracting and pre-processing image data from both infrared and visible light sources before applying the multivariate analysis. The system pre-processes the images to identify temperature defect locations and surface defect locations, then prepares correlated data for analysis. This preliminary action reduces the complexity of the subsequent multivariate analysis by providing structured, pre-processed input data, thereby improving reliability without proportionally increasing system 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
The combined analysis significantly reduces false positives by accurately identifying the cause of temperature defects, distinguishing between actual structural issues and surface irregularities.
Implementation Method 1
an infrared thermal image that is a captured image of a structure to be inspected
Implementation Method 2
a visible image that is a captured image of the structure to be inspected
Data Source
AI summary
Provided are an image analysis apparatus, an image analysis method, and a program that can reduce erroneous detection of defective portions. An image analysis apparatus includes a processor. The processor is configured to acquire an infrared thermal image that is a captured image of a structure to be inspected, acquire a visible image that is a captured image of the structure to be inspected, determine a temperature defect from the infrared thermal image, and estimate a cause of the temperature defect on the basis of, for the temperature defect, at least temperature defect information obtained from the infrared thermal image, and surface defect information obtained from the visible image.