A real time change detection technique is proposed in order to detect the moving objects in a real image sequence. The described method is independent of the illumination of the analyzed scene. It is based on a comparison of corresponding pixels that belong to different frames and combines time and space analysis, which augments the algorithm’s precision and accuracy. The efficiency of the described technique is illustrated on a real world interior video sequence recorded under significant illumination changes.
Top2. Methodology
Image sequence 
consisting of N video frames is observed. The sliding mask 
is applied on every frame.
Skifstad and Jain, (Skifstad, 1989), use the ratio of pixel intensities in mask 
between two a reference and a current frame to estimate the pixel variance 
as follows:
,
.
(1)Here, pixel intensities within mask 
are denoted with 
for a reference, background frame that does not contain changing regions and with 
for a current frame where moving objects are being identified. The mean of the pixel intensity ratio within 
is denoted with
. If 
(where 
is a suitable threshold), the center of the mask 
is marked as changing region.
Experiments in (Inigo, 1989), (Mecocci, 1989), (Rourke, 1990), (Fathy, 1995), (Corall, 1991), (Foresti, 1998), (Foresti, 1994) have shown that for significant illumination changes this method fails, i.e. some pixels are falsely assigned to changing regions. A modified technique based on adaptive coefficient for illumination compensation is proposed in this chapter. Pixel variance is estimated as:
(2)