Estimating the distribution of particle dimensions from electron microscope images

Petri Hirvonen; Heikki J. Huttunen; Maija Lappi

doi:10.1117/12.587487

1 March 2005 Estimating the distribution of particle dimensions from electron microscope images

Petri Hirvonen, Heikki J. Huttunen, Maija Lappi

Proceedings Volume 5672, Image Processing: Algorithms and Systems IV; (2005) https://doi.org/10.1117/12.587487
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

An approach for estimating the distribution of soot particle dimensions from electron microscope images is studied. We have implemented simple image-analytical methods that produce an equivalent diameter distribution which can be compared with the corresponding distribution acquired via physical measurements. In comparison with manual object detection with conventional image processing software our method is time-saving and efficient. The shape of the particles emitted from the motor under different loads is affected by phenomena in exhaust dilution or release to air. Particle shape has a significant effect on its harmfulness to health. The researchers are also interested in knowing the actual particle size distribution to be able to improve catalyzer functionality. Engine exhaust particle emissions are often analyzed by methods based on the physical properties of soot particles, and assumptions about their size and shape. Our method provides data for refining these results. The implemented graphical user interface is semi-automatic and allows the user to remove erroneous results from the resulting thresholded image before the analysis. Then the task is to calculate the properties of interest over the particle population. We have written a toolbox with simple functions that realize the semi-automated analysis and the user interface for easy operation.

Citation Download Citation

Petri Hirvonen, Heikki J. Huttunen, and Maija Lappi "Estimating the distribution of particle dimensions from electron microscope images", Proc. SPIE 5672, Image Processing: Algorithms and Systems IV, (1 March 2005); https://doi.org/10.1117/12.587487

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