Image Processing System for Microscope Frame Indexing
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Solution Overview
Problem
Current microscope systems require significant time to determine and assess specific portions of interest in moving images, as users need to review and fast-forward through extensive footage to locate frames with significant changes, which is inefficient.
Innovation Solution
An image processing system that includes an image data storage section, a display section, a region-of-interest setting section, a change amount detection section, and an index storage section, which allows users to set a region of interest, detect changes between adjacent frames, and store frames with significant changes as indices for efficient observation and assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually review and fast-forward through moving images to determine portions of interest, then they can identify frames with significant changes, but the operation requires a large amount of time
Solution Approach 1:
The system performs preliminary automated analysis of the moving image to generate index information indicating frames with significant changes before user observation. This preliminary action eliminates the need for manual fast-forwarding and review, directly resolving the time consumption issue while maintaining detection accuracy through automated change detection algorithms
Solution Approach 2:
Index information serves as an intermediary between the raw moving image data and user observation. This intermediary provides pre-processed guidance about which frames contain significant changes, allowing users to efficiently locate portions of interest without manually reviewing entire sequences, thus reducing observation time while preserving detection precision
2Productivity
If automatic detection is performed by adding indices to frames with large overall image changes, then observation efficiency is improved, but detection accuracy for user-desired frames is insufficient
Solution Approach 1:
The detection approach is segmented into multiple levels: overall image change detection for efficiency and region-of-interest change detection for accuracy. By dividing the analysis into different spatial and functional segments, the system achieves both high observation efficiency through automated indexing and high detection accuracy through focused regional analysis
Solution Approach 2:
The system applies different detection qualities to different regions: automated overall change detection provides broad coverage for efficiency, while localized region-of-interest analysis provides precise detection for user-desired frames. This local quality differentiation ensures that computationally intensive high-precision detection is applied only where necessary, maintaining both productivity and measurement precision
Data Source
AI summary
An image processing system is provided that includes: an image data storage section that stores image data of a consecutive plurality of frames; a display section that displays image data that is stored; a region-of-interest setting section that sets a region of interest in the displayed image data; a change amount detection section that, with respect to the region of interest that is set, compares image data of adjacent frames stored in the image data storage section and detects a change amount therebetween; a change determination section that determines whether the detected change amount exceeds a predetermined threshold value; and an index storage section that stores image data of a frame that is determined to exceed the predetermined threshold value by the change determination section as an index.