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Fire Detection Based on Image Processing in Coal Mine

机译:基于煤矿图像处理的火灾探测

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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.
机译:火灾探测在安全区域非常重要,始终是煤矿难题。本文提出了一种实时火灾检测器算法。在早期阶段没有明显的火焰,并且温度低,可见光稀缺,因此信号难以通过普通颜色CCD实现。这里,红外CCD用作探头,并输入的红外图像被输入计算机,然后基于图像处理确定火灾识别。首先,灰度二进制图像被熵阈值方法划分,然后通过中值过滤平滑。然后提取火焰的显着特征,并在归一化之后,前述数据输入中性网络进行识别。所有上述线索都被组合以达到最终决定。实验结果表明,该方法在检测火灾或火焰方面是成功的。此外,它显着降低了误报。还表明该方法在各种条件下工作。该系统具有很高的有效性和准确性。

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