Algorithm for particle detection and parameterization in high-frame-rate thermal video

Maxime Bombrun; Vincent Barra; Andrew Harris

doi:10.1117/1.JRS.8.083549

29 September 2014 Algorithm for particle detection and parameterization in high-frame-rate thermal video

Maxime Bombrun, Vincent Barra, Andrew Harris

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 8, Issue 1, 083549 (September 2014). https://doi.org/10.1117/1.JRS.8.083549

Abstract

Over the last decade, feature tracking and recognition in infrared (IR) video has become an important strategy used in many applications. To achieve such a capability, we developed a method based on the top-hat transform, hybridized with refinement by thresholding. Our algorithm uses two different but correlated background subtraction approaches to clean the image. A mathematical-morphology-based method was then applied to enhance the contrast between particles and background. The algorithm was tested using images acquired during a controlled experiment and was compared with another particle tracking velocimetry method. We demonstrate that our algorithm can detect dim IR targets and enables computation of a local velocity field that can be used for the tracking step. Using this method, we were able to obtain both the distribution of particle sizes, volumes (or masses), and velocities. We also apply our algorithm to images recorded during ballistic emitting explosive events at Stromboli volcano (Italy) and favorably compare our results with other volcanologic data sets. Experimental results demonstrate that our algorithm achieves a high recognition accuracy with a low-computational cost.

Citation Download Citation

Maxime Bombrun, Vincent Barra, and Andrew Harris "Algorithm for particle detection and parameterization in high-frame-rate thermal video," Journal of Applied Remote Sensing 8(1), 083549 (29 September 2014). https://doi.org/10.1117/1.JRS.8.083549

Published: 29 September 2014

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available