Image Processing System Selective Data Storage
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Solution Overview
Problem
Existing image processing systems face limitations in flexibility when setting conditions for data collection and storage, leading to inefficient data management and storage of unnecessary data, which restricts the utilization of image data post-measurement.
Innovation Solution
An image processing system that includes multiple storage parts, an imaging part, an image measuring part, a storage processing part, and a setting receiving part, allowing for flexible setting of image collection conditions and rules, including storage format and location rules, to store only relevant image data and attribute information based on predetermined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If image data is stored after measurement for later use, then data availability is improved, but storage space is consumed and data management complexity increases
Solution Approach 1:
The system extracts and stores only the essential attribute information (measurement results, feature amounts, determination outcomes) from the complete image data set. This selective extraction allows data to be stored and referenced later without requiring the full image files to be retained, significantly reducing storage space consumption while maintaining data availability for quality control purposes.
Solution Approach 2:
The system applies different storage strategies to different types of data: complete image data is stored only when collection conditions are met, while attribute information is stored systematically for all measurements. This differentiated approach optimizes storage space by allocating resources based on the specific value and usage requirements of each data type.
2Loss of information
If all image data is stored for potential future use, then data completeness is improved, but storage costs increase and data management becomes more complex
Solution Approach 1:
The system implements dynamic data management through configurable collection conditions and storage rules that can be adjusted based on actual needs. The storage processing part automatically determines what data to store by evaluating against these dynamic criteria, replacing static "store everything" or "store nothing" approaches with adaptive, context-aware data selection that reduces management complexity.
Solution Approach 2:
The system incorporates feedback mechanisms where storage decisions are based on evaluation of measurement results against predetermined criteria. The storage processing part receives feedback from the image measurement part about determination outcomes, and uses this feedback to automatically decide whether to store image data, attribute information, or both, thereby simplifying data management through rule-based automation.
3Adaptability or versatility
If flexible data collection conditions are implemented, then data selection accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments data collection flexibility into distinct, manageable components: collection conditions (triggering storage), storage rules (determining what to store), and storage formats (defining how to store). This segmentation allows each component to be configured and managed independently, reducing overall system complexity while maintaining high adaptability for different data collection scenarios.
4Quantity of substance
If only essential data is stored to save space, then storage efficiency is improved, but data availability for comprehensive analysis decreases
Solution Approach 1:
The system uses attribute information as an intermediary between complete image data and analysis requirements. Attribute information contains essential measurement results and feature amounts that serve as proxies for the full image data, enabling comprehensive analysis to be performed on stored attribute data without requiring the original large image files to be retained, thus maintaining data availability while improving storage efficiency.
Data Source
AI summary
An image processing system, an image processing device and a non-transitory computer-readable recording medium are provided. A collection condition setting part sets a collection condition for collecting processing information from the buffer area, an output format of the collected processing information, and an output destination of the collected processing information. The collecting part collects, among pieces of processing information temporarily stored in the buffer area, a piece of processing information that satisfies an image collection condition set by the collection condition setting part, and sends the collected processing information to the output part. The output part outputs the sent processing information according to an image collection rule set by the collection condition setting part. The condition setting part updates an image collection condition and an image collection rule stored in a storage condition DB on the basis of setting information input from an operation display device.