Statistics
Scientific paper
Jul 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011aspc..442..459m&link_type=abstract
Astronomical Data Analysis Software and Systems XX. ASP Conference Proceedings, Vol. 442, proceedings of a Conference held at Se
Statistics
Scientific paper
In this project, we aim to develop an efficient and reliable method to search through vast amounts of digital image data of the sky (at video rates of 30 fps) to identify meteors. We describe a pattern recognition system that accomplishes this goal in two steps. The first step keeps track of luminous objects that follow a straight path through a set of frames; multiple features become then available for each moving luminous object. During the second step, the system automatically labels the moving object as either a meteor or not (e.g., or satellite). The benefit of such a pattern recognition tool is twofold: 1) it obviates the process of searching through image data by eye, which is infeasible for producing a database with reliable statistics; 2) derived information can provide a better understanding of the mass distribution of meteors, which is crucial for determining the total mass flux incident into the upper atmosphere.
McGarvey Vilalta R. K.
Mitchell Richard
Samara M.
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