In this paper, a machine approach is applied to detect hydrocarbon fires in aircraft dry bays and engine compartments. The inputs to the machine vision system consist of a set of statistical measures derived from the histogram and image subtraction analyses of successive image frames. Specifically, heuristic rules based on the median, standard deviation and normalized first-order moment statistical measures of histogram data and the mean statistical measure of image subtraction data of successive frames are used to compute the likelihood of a fire event. This machine vision system is also tested for false alarms such as those due to flashlights and high-power halogen lights.


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    Title :

    A machine vision approach to detect and categorize hydrocarbon fires in aircraft dry bays and engine compartments


    Contributors:
    Foo, S.Y. (author)

    Published in:

    Publication date :

    2000


    Size :

    8 Seiten, 7 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English