Multi-Feature Based Fire Detection Using Video Image Processing

As fire is one of the great threats for human security fire detection systems are one of the most important components in surveillance systems used to monitor buildings and environment as part of an early warning mechanism that reports preferably the start of fire. It is very challenging for conventional fire detection systems to provide fire protection for large industrial applications and atria, such as power plants and petrochemical processing plants, shopping malls, churches, hotels, office buildings, and airports. Present work is an in depth study to detect flames in video by processing the data captured by an ordinary camera. The proposed method analyzes the frame-to- frame changes of specific low-level features describing potential fire regions. These features are color, randomness of fire area size, fire boundary roughness and saturation. Because of flickering and random characteristics of fire, these features are powerful discriminants These techniques can be used to reduce false alarms along with fire detection methods. The novel system simulate the existing fire detection techniques with above given new techniques of fire detection and give optimized way to detect the fire in terms of less false alarms by giving the accurate result of fire occurrence. The strength of using video in fire detection is the ability to monitor large and open spaces.