Sample Container Displacement Detection Using Separability Filters
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Solution Overview
Problem
Conventional methods for detecting positional displacement of a sample container on an imaging device are not accurate and efficient, especially with the increase in image data due to higher resolution imaging devices, leading to storage capacity issues and increased processing time.
Innovation Solution
A method involving the selection of two sample storage portions, calculation of logical edge coordinates, image capturing, application of a separability filter to detect temporary edge coordinates, and calculation of actual center coordinates to determine the amount of positional displacement, without requiring a template image and thus reducing data processing demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional pattern matching techniques are used to detect positional displacement, then positional displacement can be detected, but detection accuracy is low and processing time increases
Solution Approach 1:
The patent extracts only the essential features needed for displacement detection - specifically the edge coordinates of sample storage portions - rather than processing entire template images. By focusing only on edge detection and coordinate calculation, the system achieves accurate displacement measurement without the computational burden of full image pattern matching.
Solution Approach 2:
The patent segments the image processing task into distinct steps: edge detection, coordinate extraction, and displacement calculation. By dividing the problem into these manageable segments and processing only the necessary coordinates rather than entire images, the system reduces processing time while maintaining detection accuracy.
2Measurement precision
If high resolution imaging is used to capture sample images, then image quality improves, but data storage requirements increase
Solution Approach 1:
The patent extracts only the critical positional information (edge coordinates of sample storage portions) from the captured images, rather than storing and processing the entire high-resolution images. This extraction approach maintains the precision needed for displacement detection while dramatically reducing the data storage requirements.
3Measurement precision
If template image techniques are used for displacement detection, then displacement can be measured, but data processing complexity increases
Solution Approach 1:
The patent removes the complex template matching process entirely and extracts only the necessary edge coordinate information directly from captured images. This simplification eliminates the need for storing and comparing template images, reducing data processing complexity while maintaining displacement measurement accuracy through direct coordinate calculation.
Data Source
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AI summary
There is provided a method of detecting positional displacement of a sample container placed on an imaging device, at high speed and with high accuracy without increasing the amount of data required for a process. Two wells are selected (step S10) and upper, lower, left, and right logical edge coordinates of the two wells are calculated (step S20). An image of a portion near each set of logical edge coordinates is captured (step S30), and a rectangular separability filter is applied to each captured image and for each captured image, coordinates of a center position of the rectangular separability filter obtained when a peak value of a separability is obtained are detected as temporary edge coordinates (step S40). Thereafter, actual center coordinates are calculated for each well selected in step S10, based on upper, lower, left, and right temporary edge coordinates (step S60) . Finally, the amount of positional displacement of a well plate from an ideal placement state is calculated based on the center coordinates of the two wells selected in step S10 (step S70).