Fire Detection and Alarm Using Gaussian Blur Background Subtraction Technique - et. al., Bhanumathi. M , (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Fire outbreak is a major issue in oil wells, forests, houses, industries all over the world. The damage caused by these types of accidents is tremendous towards nature and humankind. After these incidents, the need for an application for fire detection has increased. However various fire detection systems use temperature or smoke sensors which takes more response time. Moreover, these systems are expensive and are not widely effective, when the fire is placed far away from the detectors. This led to various alternatives such as computer vision, image processing techniques. One of the cost-effective methods would be the usage of surveillance cameras to detect the fire to inform the relevant parties. The proposed research work suggests a method to use surveillance cameras to monitor the occurrence of fire anywhere within the camera range. In this method, an RGB color pattern and motion detection technologies are used to detect the fire by background subtraction method. The choice capacity of fire-pixels is concluded by the force and immersion of the R part. It has been used that finds the boundary of the moving region in the color segmented image and calculates the number of fire pixels in this area. At that point, a fire identification framework is created dependent on this technique to identify fire effectively to spare life and property from fireperil.