Exploit the particle tracking capabilities of the algorithm

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The global pipeline of the DIH-PTV spatio-temporal particle flux reconstruction algorithm. Given a single-shot holographic image, the spatial particle volume and temporal fluid flow are obtained simultaneously by solving the difficult inverse problem equation (6) by alternating optimization of the custom solver using prior distribution specific to the domain. Made. Credit: DOI: 10.1002 / lpo.202100008

A simple camera system combined with sophisticated image processing algorithms can reconstruct the particle stream faster and more accurately.

By replacing complex hardware parameters with simple hardware combined with optimized image processing, KAUST researchers have developed a faster and more accurate three-dimensional (3D) particle tracking system.

The observation of the 3D motion of particles in a stream is important in studies of aerodynamic, hydrodynamic and molecular dynamics. Traditionally, this has been done using a complex arrangement of multiple cameras, from which images are analyzed and compared to reconstruct the movement of individual particles in 3D space over time. However, such 3D particle velocity measurement systems are often bulky, expensive and difficult to use due to their complex configuration, frequent and tedious calibrations.

Holography offers a promising and simpler alternative. In this approach, the particles are illuminated by laser beam The images of the particles are captured with a single camera. As the laser light is diffracted around each particle, the 3D position of the particle can be ring diffraction in the image. However, while the hardware for such systems is well established, the software to reconstruct the particle flow is still in its infancy.

Ni Chen and Congli Wang of KAUST of Wolfgang Heidrich’s group have developed an optimized particle motion reconstruction algorithm that can greatly expand the adoption of digital holographic measurements of particle velocity.

“Inline holography requires fewer components, is much easier to set up, is easier to use with a microscope, and offers higher spatial resolution, but is difficult to solve digitally,” says Wang. to augment. “We have shown that by using advanced software algorithms we can achieve the same or better performance than traditional methods.”

Previous particle motion reconstruction algorithms analyzed the position and motion of particles in separate successive steps. The research team has developed a digital algorithm called Holo-Flow that resolves both position and movement in parallel and transmits information at each step. This not only improves the accuracy and quality of the stream reconstruction, but also the Parallelize process algorithm and significantly speed up the computation.

“This study shows the potential of computer image processing in which hardware and software jointly consider the encoding and decoding of target information as a whole,” said Wang, postdoctoral researcher at the University of California, Berkeley. I am. “This method can be used in a simple inline holography setup to reconstruct a flow field in seconds instead of hours on a single GPU.”


Particle tracking in 3D? There is an app for it


For more information:
Ni Chen et al, Snapshot Space-Time Holographic 3D Particle Tracking Velocity Measurement, Examining laser and photonics (2021). DOI: 10.1002 / lpo.202100008

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King Abdullah University of Science and Technology

Quote: Https: //phys.org/news/2021-08-harnessing-particle-tracking-power-algorithm.html Algorithm particle tracking capability (August 25, 2021) obtained on August 25, 2021 To be used

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