Image Quality Screening for Composite Inspection Re-Shooting
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Solution Overview
Problem
Existing image-based inspection methods for structures face challenges in determining the quality of captured images and efficiently identifying areas that require re-shooting due to factors like resolution, focus, and blurring, especially when conducted by inspectors facing labor shortages.
Innovation Solution
An information processing apparatus that evaluates image quality based on shooting resolution, focus, and blurring, generates composite images using high-quality images, and provides notifications for re-shooting areas with missing pixels or poor quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image-based inspection is performed using high-definition cameras to detect deformations, then measurement precision is improved, but the complexity of processing and evaluating numerous shot images increases device complexity
Solution Approach 1:
The system performs self-evaluation by automatically assessing image quality metrics (sharpness, exposure, focus) and identifying suitable images for composite generation without human intervention, enabling the system to serve itself in quality control
Solution Approach 2:
Manual image quality assessment by inspectors is replaced with automated computer-based evaluation algorithms that objectively measure image qualities such as sharpness, exposure accuracy, and focus, substituting human mechanical judgment with computational analysis
2Area of stationary object
If multiple shot images are stitched to generate large-scale composite images, then the coverage area increases, but the time required for image processing and composite generation increases loss of time
Solution Approach 1:
Image quality evaluation is performed in advance during the image acquisition phase, identifying suitable images before composite generation begins. This preliminary assessment prevents wasted processing time on low-quality images and streamlines the subsequent composite generation workflow
Solution Approach 2:
The large-scale inspection area is divided into multiple shot images that are processed and evaluated independently, then selectively combined into composites. This segmentation allows parallel processing of individual images, reducing overall processing time while maintaining comprehensive coverage
3Measurement precision
If manual inspection by civil engineers is performed, then judgment accuracy is maintained, but productivity decreases due to labor shortages
Solution Approach 1:
The system autonomously evaluates image quality, generates composites, and produces inspection reports without requiring manual review, enabling the inspection process to serve itself and eliminate dependency on limited human resources while maintaining consistent quality standards
Solution Approach 2:
Manual inspection activities are replaced with automated image processing and analysis systems that objectively evaluate structural conditions, substituting human physical inspection with computational methods that can process images faster and without fatigue
Data Source
AI summary
An information processing apparatus including a storage unit configured to store pieces of image quality information, respectively, for a plurality of images that show a subject, a determination unit configured to determine whether image qualities of the images are favorable based on the pieces of image quality information of the images, a composition unit configured to generate a composite image using images that have been determined to have favorable image qualities by the determination unit, and a notification unit configured, in a case when there is a missing pixel area in the composite image, to provide a notification about a re-shooting method for the subject corresponding to the missing pixel area, wherein the determination unit determines whether the image qualities of the images are favorable based on a shooting resolution, focus, and blurring.