## The basics of background substraction

This tutorial explain the basics of background substraction. First of all we need define what is a background and what is a foreground.

We consider a background the pixels of image without motion. And a foreground the pixels with motion. Then the simplest background model assume each background pixel his brightness varies independently with normal distribution. Then we can calculate our statistical model of background by accumulating several dozens of frames and his squares, this is:

$latex \displaystyle{S(x,y)=\sum_{f=1}^N p(x,y)}$
$latex \displaystyle{Sq(x,y)=\sum_{f=1}^N p(x,y)^2}$

Published: By: David Millán Escrivá - 5:20 PM