High-Speed Microbubble Imaging Segmentation for Overlap Resolution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for morphological identification and trajectory tracking of high-concentration microbubbles face challenges due to image overlapping and boundary blurring, leading to inaccurate particle size distribution and velocity field calculations, which affects noise attenuation analysis in underwater environments.
Innovation Solution
A high-speed imaging method using a CMOS camera with pre-processing techniques such as binarization, noise removal, and erosion, combined with distance transformation and watershed transformation, to segment and identify microbubble images, calculate particle size distribution, and track motion trajectories and velocities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional low-velocity imaging method is used, then device complexity is reduced, but time resolution is insufficient to capture bubble motion patterns
Solution Approach 1:
The patent changes the temporal parameter by using high-speed imaging to capture images at extremely short time intervals (microsecond level), transforming the imaging system from low-velocity to high-velocity mode to resolve the motion patterns of microbubbles in the flow field
2Speed
If high-speed imaging is used to capture microbubble motion, then time resolution is improved, but image overlapping and boundary blurring occur in high-concentration regions
Solution Approach 1:
The patent applies image segmentation techniques to divide the high-concentration microbubble field into individual bubble regions, separating overlapping boundaries through computational methods to restore morphological accuracy despite high imaging speed
Solution Approach 2:
The patent transitions from 2D image analysis to 3D spatial-temporal analysis by incorporating time dimension, using multi-frame image sequences to track and distinguish individual bubbles through their motion trajectories, thereby resolving overlapping issues in high-concentration regions
3Measurement precision
If traditional acoustic dispersion method is used to measure microbubble parameters, then measurement capability is provided, but test environment requirements are high and implementation is complex
Solution Approach 1:
The patent replaces the traditional acoustic dispersion measurement system with an optical imaging system, substituting acoustic field-based measurement with light field-based imaging and image processing, thereby simplifying the test environment while maintaining measurement capability
Solution Approach 2:
The patent creates visual copies (images) of microbubbles through optical imaging, allowing parameter extraction from image data rather than requiring direct acoustic measurement, which simplifies the experimental setup and data acquisition process
Data Source
AI summary
A method for morphological identification, trajectory tracking, and velocity measurement of high-concentration microbubbles, includes collecting images of a microbubble group, performing image pre-processing, segmenting overlapped pixel blocks of the image of the microbubbles, identifying the image of the microbubbles, obtaining morphological information of each of the microbubbles, obtaining an equivalent diameter of each of the microbubbles, calculating a size distribution of the microbubbles; correlating the images of the microbubbles at two adjacent instants, and obtaining a velocity field and motion trajectory of the microbubbles. The method applies to morphological identification and correlation of high-concentration microbubbles and obtains the particle size distribution and velocity field information of the microbubbles.