Survey on Background Modeling and Foreground Detection for Real Time Video Surveillance

AbstractIn Image Processing, a very trivial task is to detect the changes in the multiple images of the same scene of a real time instant. The task is not only trivial but also very indispensable as it brings into play a great number of diversified subject area applications such as, remote sensing, surveillance, medical diagnosis and treatment, security surveillance, and underwater sensing. The main perspective of this survey is to give a nomenclature study of the general processing steps and prime decision rules used in the advanced change detection algorithms, which are employed for the real time video surveillance. The real time video surveillance models encompass the predictive and the background modelling techniques. The survey also emphasizes on the comparison of the processing speed of the various change detection algorithms applied in real time video surveillance