Event-Based Camera Particle Measurement via Reference Lines
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing direct imaging systems for measuring particle attributes, such as concentration and size, are limited by complex image processing and low frame rates, making them unsuitable for real-time analysis and applications like continuous process monitoring, especially in constrained environments like inkjet printers where droplets are projected at high speeds.
Innovation Solution
Utilizing an event-based camera with a sensor array oriented perpendicularly to the particle trajectory, employing reference rows to measure longitudinal speed and size by analyzing event rates and converting space-time coordinates to spatial coordinates, and employing multiple thresholds and averaging to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a high definition, high magnification camera is used to record particles, then measurement precision is improved, but frame rate decreases making real-time analysis difficult
Solution Approach 1:
The patent segments the particle trajectory into two distinct measurement zones defined by reference lines R1 and R2. By dividing the measurement process into discrete spatial segments with specific detection points, the system achieves high precision particle attribute measurement while maintaining high frame rate capability through the event-based camera's asynchronous sampling approach.
2Measurement precision
If complex image processing is used to analyze recorded video, then measurement accuracy is improved, but processing time increases reducing real-time capability
Solution Approach 1:
The patent extracts only the essential information needed for particle measurement by using reference lines R1 and R2 to define specific regions of interest. Instead of processing entire video frames, the system extracts temporal distances between events at these reference lines, dramatically reducing processing time while maintaining measurement accuracy for particle attributes such as velocity and size.
Solution Approach 2:
The patent changes the measurement parameters from full-frame image analysis to temporal distance measurement between events at specific reference lines. This parameter transformation enables real-time processing by converting complex spatial image processing into simpler temporal interval calculations, achieving both high accuracy and real-time performance.
3Ease of operation
If standard frame-based cameras are used, then ease of operation is maintained, but ability to measure fast-moving particles in constrained regions deteriorates
Solution Approach 1:
The patent employs an event-based camera that dynamically adapts its sampling rate to the speed of particles passing through the measurement region. Instead of fixed frame rates, the system continuously samples at variable rates based on event detection, enabling accurate measurement of fast-moving particles while maintaining operational simplicity through automated dynamic adjustment.
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
Enables real-time measurement of particle attributes with reduced processing complexity, suitable for fast-moving particles in constrained regions, and can differentiate multiple particles crossing simultaneously.
Implementation Method 1
an event-based sensor oriented such that lines of a pixel array of the sensor lie across an expected trajectory of the particle through the region of interest
Data Source
Figure 1~3
Figure 4~6
Figure 7~8B
AI summary
A method for measuring attributes of a particle in motion comprises observing a region of interest with an event-based sensor oriented such that lines of a pixel array of the sensor lie across an expected trajectory of the particle (P) through the region of interest; defining two reference lines of pixels (R1, R2) separated by a spatial distance (D); sampling a first group of events produced by a first of the two reference lines; sampling a second group of events produced by the second of the two reference lines; determining a temporal distance (T) between the second and first groups of events; and providing a longitudinal speed factor (vy) of the particle based on the spatial distance and the temporal distance. The particles have a size spanning multiple adjacent pixels in a line, and the method further comprises analyzing one of the first and second groups of events over multiple time steps in order to produce an outline of the particle in space-time coordinates (x, t) including spatial components based on positions of event-triggered pixels in the lines and temporal components based on the time steps; and converting the space-time coordinates of the outline to spatial coordinates (x', y') by multiplying the time steps (t) of the space- time coordinates by the longitudinal speed factor (vy).