Improved background subtraction techniques for security in video applications

This paper attempts to find moving objects by subtracting the background images from static single camera video sequences in security systems. It aims to improve the background subtraction techniques for indoor video surveillance applications. For dynamic video sequences, the object focus and object tracking are very difficult due to changing of various parameters such as camera noise, illumination changes, motion changes, and geometry of background changes. The background subtraction algorithm provides the solution to detect moving objects in the static scene. The recursive and non-recursive algorithms are discussed in an improved way. The novel automatic threshold updating (ATU) algorithm is also developed and tested for various indoor video sequences which gives better efficiency. The statistical and temporal differencing methods are also presented. Finally, our novel approach is compared with the existing methods.