Image Sample Traceability Using Cut-Out Position and Evaluation Links
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Solution Overview
Problem
Existing image management systems fail to associate parent samples with their cut-out positions and evaluation results effectively, making it difficult to manage parent and child samples suitably.
Innovation Solution
An image management system that includes storage sections for first and second sample images, evaluation results, and cut-out position information, associating these elements with each other.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only basic cut-out position information is stored, then storage simplicity is maintained, but the association between parent sample and evaluation result is insufficient
Solution Approach 1:
The data storage is segmented into multiple structured fields: parent sample ID, child sample ID, cut-out position coordinates, cut-out direction, and evaluation results. This segmentation allows comprehensive information association while maintaining organized and manageable data structures.
Solution Approach 2:
The patent introduces an intermediary data structure (management table) that links parent samples and child samples through multiple parameters. This intermediary table serves as a mediator that establishes comprehensive associations between parent and child samples without requiring direct complex relationships.
2Measurement precision
If comprehensive information is stored for each sample, then evaluation accuracy is improved, but data management complexity increases
Solution Approach 1:
The patent applies local quality by storing specific relevant information for each sample type: parent samples store imaging results and defect information, while child samples store evaluation results. Each data field contains only the necessary quality information for its specific purpose, avoiding unnecessary complexity.
Solution Approach 2:
The patent adds multiple dimensions to the data structure including spatial coordinates (X, Y positions), directional information, and hierarchical relationships (parent-child sample links). This multi-dimensional approach organizes comprehensive information in a structured manner that improves evaluation accuracy while maintaining manageability.
Data Source
AI summary
An image management system includes a first storage section, a second storage section, and a third storage section. The first storage section stores a first image of a first sample related to quality information. The second storage section stores an evaluation result of a second sample cut out from the first sample. The third storage section stores information on a cut-out position of the first sample or the second sample and a feature amount at a position selected from the first image. The first image, the evaluation result of the second sample, the information on the cut-out position, and the feature amount are associated with each other.