Computer Vision Based Fire Detection System Using OpenCV - A Case Study

Conventional fire detection system was based mechanical sensor for fire detection. The smoke particles in the surrounding detected by sensors in the traditional fire detection system. However, this can also lead to false alarms. For example, a person smoking in a room of can activate a general fire alarm system. In addition, these systems are expensive and ineffective if the fire is far away from the detector. An alternatives fire detection system such as system based on computer vision and Image/video Processing technology to manage false alarms from conventional fire detection. One of the most cost-effective ways is to use surveillance cameras to detect fires and alert affected parties. In the following proposed system proposes a technique which will be monitor the outburst of a fire anywhere within the camera range using a surveillance camera. In this Paper, fire alarm system will be developed to efficiently detect fires and protect lives and property from fire hazards. This research describes a fire detection system that uses color and motion models derived from video sequences. The proposed approach identifies color changes and mobility in common areas to identify fires and can therefore be used both in real time and in datasets.