Open AccessDIGITAL IMAGE ANALYSIS OF BURNING DROPLETS IN THE PRESENCE OF BACKLIGHT DIFFRACTION AND SOOT
Author(s) -
Ramya Bhaskar,
Benjamin D. Shaw
Publication year - 2019
Publication title -
image analysis and stereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 27
eISSN - 1854-5165
pISSN - 1580-3139
DOI - 10.5566/ias.2015
Subject(s) - outlier , backlight , soot , enhanced data rates for gsm evolution , combustion , materials science , diffraction , image (mathematics) , computer vision , optics , computer science , artificial intelligence , liquid crystal display , chemistry , physics , optoelectronics , organic chemistry
Approaches for analyzing digital images of moving and burning fuel droplets, with the goal of accurately measuring droplet edge coordinates, are discussed. Strategies for locating droplet edges in the presence of obscuration from soot and also backlight diffraction at the droplet edge are described. An outlier detection method is employed to identify outliers in droplet edge coordinates, and the resulting data can have significantly smaller standard deviations in droplet diameters if outliers are rejected, especially for droplets that exhibit significant soot formation. The approaches described herein are applied to images from droplet combustion experiments performed on the International Space Station as well as to synthetic image sequences that were generated to enable the accuracy of the algorithms to be assessed.