CCTV surveillance systems are widely used as a street monitoring tool in public and private areas. This
paper presents a novel approach of an intelligent surveillance system that consists of adaptive background
modelling, optimal trade-off features tracking and detected moving objects classification. The proposed
system is designed to work in real-time. Experimental results show that the proposed background
modelling algorithms are able to reconstruct the background correctly and handle illumination and adverse
weather that modifies the background. For the tracking algorithm, the effectiveness between colour,
edge and texture features for target and candidate blobs were analysed. Finally, it is also demonstrated
that the proposed object classification algorithm performs well with different classes of moving objects
such as, cars, motorcycles and pedestrians.