Image Defect Detection Parameter Adjustment by Region Segmentation
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Solution Overview
Problem
Existing image processing techniques require users to manually set parameters for each region of an image, which can be cumbersome, especially for large images, and often result in inefficient or incorrect parameter settings due to the need for visual inspection of dispersed regions.
Innovation Solution
An apparatus and method that allows users to specify a first region for correction, adjusts parameters accordingly, and determines second regions based on image attributes, applying the adjusted parameters to these regions, thereby simplifying the process and ensuring appropriate parameter application across the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parameters are set for each region by visual inspection, then parameter accuracy is improved, but user operation complexity increases
Solution Approach 1:
The system automatically determines the second region and applies parameters without requiring user specification of each region. The determination unit autonomously identifies which regions should receive the adjusted parameters based on the first region's characteristics, eliminating the need for manual region-by-region parameter setting while maintaining accuracy.
Solution Approach 2:
The image is divided into multiple candidate second regions, and the determination unit selects appropriate regions from these segments. This segmentation approach allows the system to efficiently identify target regions without requiring the user to manually inspect and specify each region individually.
2Manufacturing precision
If parameters are adjusted for each dispersed region, then processing accuracy is improved, but processing time increases
Solution Approach 1:
Multiple parameter adjustments that would otherwise be performed separately for different regions are merged into a single operation. By adjusting parameters for the first region and automatically determining applicable second regions, the system combines what would be multiple discrete adjustment operations into one unified process, significantly reducing processing time while maintaining accuracy.
Solution Approach 2:
The system performs preliminary determination of the second region based on the first region's characteristics before applying parameters to multiple regions. This preliminary action allows the system to prepare the parameter application strategy in advance, avoiding repeated analysis and adjustment operations for each region.
3Adaptability or versatility
If users specify multiple regions for parameter setting, then parameter applicability is improved, but operation complexity increases
Solution Approach 1:
The determination unit automatically identifies and selects the appropriate second regions where the adjusted parameters should be applied, based on the characteristics of the first region. This self-service mechanism eliminates the need for users to manually specify multiple regions, reducing operation complexity while ensuring parameters are applied to all relevant regions for maximum adaptability.
Data Source
AI summary
An apparatus includes a display control unit, a receiving unit, an adjusting unit, and a determination unit. The display control unit is configured to display an image showing a result of detection of a defect from a captured image of a structure on a display device. The receiving unit is configured to receive an operation to specify part of the displayed image as a first region and an operation to give an instruction to correct at least part of the detection data corresponding to the first region. The adjusting unit is configured to adjust a parameter to be applied to the first region according to the instruction. The determination unit is configured to determine one or more second regions to which the adjusted parameter is to be applied from a plurality of segmented regions of the image.