Moving object detection in video processing plays a very important
role in many vision applications. The vision systems that include
image processing methods are widely implemented in many areas as
traffic control, video surveillance of unattended environments,
etc. Most of the existing algorithms for moving object detection
assume that the illumination in a scene remains constant.
Unfortunately, this assumption is not valid, especially in outdoor
environment. The efficiency of some of existing techniques
diminishes significantly if the illumination varies. The problems
associated with the background-based moving object detection
techniques are mainly due to the variations of ambient lighting.
Two effective moving object detection algorithms, based on the
shading model method, are described. They showed to be robust under
the conditions of extreme illumination variations unlike the other
existing methods. The new methods are shown to be invariant to
significant illumination changes and superior to other techniques
when the illumination is allowed to vary.
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