Bright-Field Inspection for Bacteria Aggregates and Foreign Matter
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Solution Overview
Problem
Existing methods struggle to accurately distinguish between isolated bacteria, aggregated bacteria, and foreign matters such as dust, dirt, and air bubbles in bacterial proliferation tests, leading to erroneous detection of bacterial proliferation.
Innovation Solution
An inspection device and method that utilizes image processing techniques, including binarization, contour extraction, and integrated signal difference analysis to differentiate between foreign matters and fine particle aggregates and accurately detect their presence and the degree of proliferation of fine particles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If label-free detection method using bright-field microscope is used, then reagent costs are reduced, but foreign matters such as dust, dirt, and air bubbles are misdetected as bacteria
Solution Approach 1:
The patent segments the detection process into multiple stages: initial image capture, foreign matter detection through binarization, contour extraction, and fine particle region detection. By dividing the detection workflow, the system can identify and exclude foreign matters while detecting bacteria, maintaining detection accuracy without using fluorescent reagents
Solution Approach 2:
The patent introduces image processing algorithms as an intermediary between the bright-field microscope and the detection result. The binarization and contour extraction processes act as mediators that differentiate between foreign matters and bacteria based on image characteristics, enabling accurate detection without fluorescent labeling
2Measurement precision
If image processing is performed to detect bacterial proliferation, then detection sensitivity is improved, but it becomes difficult to distinguish between aggregated bacteria and foreign matters
Solution Approach 1:
The patent applies dynamic thresholding in the binarization process, adapting the threshold based on local image characteristics. This allows the system to maintain high sensitivity for detecting bacteria while dynamically adjusting to distinguish aggregated bacteria from foreign matters based on their different image patterns
Solution Approach 2:
The patent applies different image processing operations to different regions of the image. By performing contour extraction and binarization with locally adapted parameters, the system can distinguish between aggregated bacteria and foreign matters in different image regions while maintaining overall detection sensitivity
3Measurement precision
If binarization and contour extraction are performed to detect fine particles, then detection capability is improved, but foreign matters are still erroneously detected as bacteria
Solution Approach 1:
The patent performs preliminary foreign matter detection through binarization before the main fine particle detection process. By identifying and excluding foreign matter regions in advance, the subsequent contour extraction and fine particle detection operate only on valid bacterial regions, improving both capability and reliability
Solution Approach 2:
The patent extracts and removes foreign matter regions from the image through the binarization process before performing fine particle detection. By taking out the problematic foreign matter components, the system prevents erroneous detection while maintaining the ability to detect actual bacteria
Data Source
Figure 1A~1C
Figure 2~3A
Figure 3B~4
AI summary
Provided is an inspection device that can detect foreign matter and fine particle aggregates, and can accurately detect the degree of proliferation of fine particles. An inspection device 500 for aggregates comprises an image acquisition unit 11 that acquires an image of the inside of a container 511 holding a liquid containing fine particles, and detects the presence or absence of a fine particle aggregate. The inspection device 500 comprises: a foreign matter presence/absence determination unit 24 that binarizes an image, creates a first binarized image, and determines the presence or absence of foreign matter; a fine particle region detection unit 25 that extracts contours of the image to produce a contour-extracted image, binarizes a composite image of the extracted contour-extracted image and the image, creates a second binarized image, and detects a fine particle region; an integrated signal difference processing unit 16 that calculates the difference value between a first integrated signal, which was obtained by integrating the first binarized image, and a second integrated signal, which was obtained by integrating the second binarized image; and an aggregation presence/absence determination unit 17 that determines the presence or absence of aggregates by numerically analyzing the difference waveform of the difference value. The inspection device detects the presence or absence of at least two different types of objects contained in the image.