Early Fire Detection for High Space Based on Video-Image Processing

In high space fire is one of the great threats for human security. The previous temperature-sensed and smoke-sensed method can´t respond quickly to early fire, and the fire may not be detected immediately if it is far away from the sensors. Therefore, double band infrared vision-based fire detection is adopted to overcome the drawbacks of traditional detection equipments for high space. Firstly, a region partition algorithm is proposed, which improves the recognition efficiency. The flame features are extracted and normalized, and then a BP neural network model is established for recognition combined with image processing. The experimental results demonstrate that the proposed method can distinguish fire effectively and improve the accuracy. In addition, the false alarms rate issued to traditional approach can be reduced drastically. This approach has short response time and strong robustness.