Detection of fire using image processing techniques with LUV color space

Vision based fire detection system have recently gained popularity as compared to traditional fire detection system based on sensors. The popularity and need of video surveillance at residential, Industrial, public and business locations have supported the widespread use of vision based fire detection system. The colour of fire is the basic technique for identification of fire in an image. However, the colour of fire varies from red, orange, yellow to white. Also, there are non-fire objects with fire-like colour. In order to improve the accuracy of fire detection system, colour detection is combined with various other techniques. Edge detection, motion detection, area covered by flames, existence of smoke, growth of fire and background segmentation are some techniques which are combined by various researchers and used to correctly classify the fire images and fire-like non fire images in a video. There are also various thresholds that are used to differentiate fire in any frame. These thresholds need to be adjusted based on the type of area and its brightness level. Also, the difference in the subsequent frames and area covered by the flames supports the existence of fire if it is greater than the threshold. This paper presents the comparative analysis of five recent vision based fire detection system. These fire detection systems are based on flame colour detection combined with other features such as motion and area of frame. The fire detection system based on LUV colour space and hybrid transforms is proposed.