Voting schemes include unanimity voting, majority voting, and
m-out-of-n voting in which an output choice is accepted if at least
votes agree with the decisions of
sensors [18]. We
use a variant of
-out-of-
voting, the so-called
-out-of-
voting in which the output is accepted if
where the
's are user-defined weights, the
's are decisions of
the four stages of the algorithm, and
is a user-defined threshold.
Decision parameter
can take binary values 0 and 1, corresponding
to normal case and the existence of fire, respectively. The decision
parameter
is 1 if the pixel is a moving pixel, and 0 if it is
stationary. The decision parameter
is taken as 1 if the pixel
is fire-colored, and 0 otherwise. The decision parameter
is 1
if the number of zero crossings of
and/or
in
a few seconds exceed a threshold value, and 0 otherwise. The decision
parameter
is defined in Equation (
).
In uncontrolled fire, it is expected that the fire region should have
a non-convex boundary. To gain a further robustness to false alarms,
another step checking the convexity of the fire region is also added
to the proposed algorithm. Convexity of regions is verified in a heuristic manner. Boundaries of the regions in the mask are checked for their convexity along equally spaced five vertical and five horizontal lines using a
grid. The analysis simply consists of checking whether
the pixels on each line belong to the region or not. If at least three
consecutive pixels belong to the background, then this region violates
the convexity condition. A
mask region which has background pixels on the intersecting vertical and/or horizontal lines, is assumed to have a non-convex boundary. This eliminates false alarms due to match light sources, sun, etc.