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29 September 2014 Algorithm for particle detection and parameterization in high-frame-rate thermal video
Maxime Bombrun, Vincent Barra, Andrew Harris
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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.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
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).
Published: 29 September 2014

Cited by 10 scholarly publications.
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