Accidental fire always causes great loss. If that fire is detected in time, then loss can be minimized. Hence there should be more efficient systems to avoid losses. Most of the fire detection systems are based on sensors. These sensors give false alarms in case of cigarette or essence sticks are burnt and these systems are also quite costly. By using fire detection system through video surveillance cameras the cost of system can be reduced. The videos achieved by popular surveillance cameras are analysed and different topologies of information, respectively based on colour and movement are united into a multi expert system in order to increase the overall accuracy of the approach, making it possible its usage in real time applications. The systems use HSV, HSL, YUV models. In these systems, the models are based on colour, motion and shape. The approaches have been tested on a wide database with the aim of assessing its performance both in terms of sensitivity and specificity
