Fine Particle Detection via Contour Extraction and Logical Operations
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Solution Overview
Problem
Existing methods for detecting fine particles in biological samples, such as bacteria, face challenges in accurately recognizing fine particle regions due to changes in particle shape and number, especially when the particles overlap or are distributed in the focal direction of a microscope.
Innovation Solution
A testing apparatus and method that involves capturing images of fine particles using a bright field microscope, performing contour extraction, and executing logical operations on these images to determine the presence and extent of fine particles, thereby preventing erroneous recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If binarization is used to recognize fine particles in microscopic images, then fine particle discrimination is enabled, but erroneous recognition occurs when particles are densely packed or overlapping
Solution Approach 1:
The patent divides the image processing into multiple stages: first performs contour extraction to identify particle boundaries, then performs binarization based on these contours. This segmentation of processing steps allows accurate particle recognition even when particles are densely packed or overlapping, as the contour extraction phase separates particles that simple binarization would conflate into a single mass.
Solution Approach 2:
The patent performs contour extraction as a preliminary action before binarization. By first identifying the contours of fine particles through edge detection and boundary tracing, the system prepares a structured representation of particle locations and shapes. This preliminary contour map then guides the subsequent binarization process, ensuring that particles are correctly segmented even in dense arrangements where direct binarization would fail.
2Productivity
If simple binarization is applied to all images, then processing speed is maintained, but accurate detection fails when particle distribution varies significantly
Solution Approach 1:
The patent implements dynamic image processing that adapts to varying particle distributions. The system automatically selects between contour extraction-based processing and direct binarization based on image characteristics such as particle density and contrast. This dynamic adaptation maintains processing efficiency while ensuring accurate detection across different experimental conditions, adjusting the processing depth to match the actual measurement needs.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate determination of the degree of increase in fine particles, even in cases where the particles are densely packed or overlapping, thereby improving the reliability of fine particle detection and analysis.
Implementation Method 1
capturing images of fine particles using a bright field microscope
Data Source
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AI summary
Provided is a technique for preventing erroneous recognition of a fine particle region from a captured image of fine particles. A fine particle testing apparatus of the present disclosure includes: an imaging part capturing a first fine particle image of a well that holds a liquid containing fine particles; an image processor executing a process of generating a second fine particle image by extracting a contour of the first fine particle image, a process of performing a logical operation between the first fine particle image and the second fine particle image, a process of calculating a feature amount of the fine particles based on a result of the logical operation, and a process of determining growth of the fine particles in the well based on the calculated feature amount; and an output part outputting a result of the determination