Microscope Image Processing Using Saturation Thresholds
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Solution Overview
Problem
Existing microscope techniques require manual focus adjustment and visual verification to detect sample regions, especially at high magnification, which can be cumbersome and inefficient, especially when the sample is in an out-of-focus state.
Innovation Solution
An image processing apparatus that captures images using a microscope, extracts color information, particularly saturation values, to automatically detect regions corresponding to an observation target, allowing for easy identification of sample regions regardless of focus state by setting a predetermined saturation threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual focus adjustment and visual verification are used to detect sample regions, then measurement precision can be maintained, but ease of operation deteriorates and time consumption increases
Solution Approach 1:
The patent replaces manual mechanical focus adjustment and visual verification with an automated image processing system that uses saturation value analysis. The detecting unit automatically identifies sample regions by comparing saturation values against threshold values, eliminating the need for manual focus adjustment and visual inspection by operators.
Solution Approach 2:
The system performs self-verification by automatically detecting sample regions through saturation analysis. The detecting unit independently identifies and confirms sample regions without requiring external manual verification, enabling the system to service itself in the detection process.
2Measurement precision
If manual focus adjustment is performed to achieve appropriate contrast value, then measurement precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces manual focus adjustment procedures with an automated saturation-based detection system. The image processing apparatus automatically analyzes saturation values to identify sample regions, eliminating time-consuming manual focus adjustment while maintaining detection accuracy.
Solution Approach 2:
The system performs preliminary saturation analysis on captured images to pre-identify potential sample regions before final detection. By预先 analyzing saturation distributions and setting threshold values in advance, the system accelerates the overall detection process without sacrificing precision.
3Measurement precision
If visual checking and designation of sample regions is required, then measurement precision is maintained, but ease of operation deteriorates
Solution Approach 1:
The patent replaces visual checking and manual designation operations with automated image processing. The detecting unit automatically identifies sample regions by analyzing saturation values and comparing them against threshold values, eliminating the need for users to visually inspect and manually designate regions.
Solution Approach 2:
The system creates a processed version of the captured image with enhanced saturation information that automatically highlights sample regions. This processed image copy serves as the basis for automated detection, replacing the need for users to visually interpret original images and manually designate regions.
Data Source
AI summary
An image processing apparatus obtains image data captured via a microscope, obtains first color information from the image data and detects a region corresponding to an observation target from the image data. The first color information is information relating to saturation, and the image processing apparatus detects a region with a value for saturation based on the first color information that is greater than a predetermined threshold as the region corresponding to the observation target of the image data.