Fire Detection Based on Image Processing in Coal Mine

Fire detection is very important in safety area, and at all times it is a difficult problem in coal mine. In this paper, a real-time fire-detector algorithm is proposed. In early stage there is no evident flame, and the temperature is low, the visible light is scarce, so the signal is difficult to achieve by ordinary color CCD. Here infrared CCD is employed as a probe, and obtained infrared image is input the computer, then fire recognition is determined based on image processing. Firstly, the grey scale binary image is partitioned by entropy threshold method and then smoothed by Median filtering. Then significant characteristics of flame are extracted and after normalization the foregoing data are input neutral network for recognition. All of the above clues are combined to reach a final decision. Experiment results show that the proposed method is successful in detecting fire or flames. In addition, it reduces the false alarms remarkably. It is also shown that the method works in a variety of conditions. The system has high validity and accuracy.