| 基于红外遥感信息的煤矿车辆 异常行为检测研究 |
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| 引用本文： | 李玉吉,曹旭辉.基于红外遥感信息的煤矿车辆 异常行为检测研究[J].中州煤炭,2021,0(12):71-76. |
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| 作者姓名： | 李玉吉 曹旭辉 |
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| 作者单位： | （陕西国防工业职业技术学院，陕西 西安 710300） |
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| 摘 要： | 为了提升煤矿车辆异常行为检测水平，设计了基于红外遥感信息的煤矿车辆异常行为检测方法。该方法引入清晰度权重以及拉伸系数实现红外遥感图像中目标煤矿车辆部位的局部增强，利用均值漂移算法跟踪增强后的红外遥感图像中目标煤矿车辆，依据煤矿车辆跟踪结果提取煤矿车辆运动方向、运动速度以及运动方向3项异常行为检测参数，采用加权融合方法处理煤矿车辆异常行为检测参数的状态函数，融合结果高于所设定阈值时，煤矿车辆存在异常行为，否则煤矿车辆为正常行驶状态。实验结果表明，该方法可利用煤矿车辆位置、车辆行驶速度以及车辆方向变化检测煤矿车辆异常行为，具有较高的应用性。
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| 关 键 词： | 红外遥感信息 煤矿车辆 异常行为 检测方法 |
Research on detection of abnormal behavior of coal mine vehicles based on infrared remote sensing information |
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| Li Yuji,Cao Xuhui. Research on detection of abnormal behavior of coal mine vehicles based on infrared remote sensing information[J].Zhongzhou Coal,2021,0(12):71-76. |
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| Authors: | Li Yuji Cao Xuhui |
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| Affiliation: | （Shaanxi Institute of Technology，Xi′an 710300，China） |
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| Abstract: | In order to improve the detection level of abnormal behavior of coal mine vehicles，a detection method of abnormal behavior of coal mine vehicles based on infrared remote sensing information was designed.This method introduced the definition weight and stretch coefficient to realize the local enhancement of the target coal mine vehicle in the infrared remote sensing image，used the mean shift algorithm to track the target coal mine vehicle in the enhanced infrared remote sensing image，and extracted the movement direction of the coal mine vehicle based on the coal mine vehicle tracking results.Movement speed and movement direction were 3 abnormal behavior detection parameters，and the weighted fusion method was used to process the state function of the abnormal behavior detection parameters of coal mine vehicles.When the fusion result was higher than the set threshold，the coal mine vehicle had abnormal behavior，otherwise the coal mine vehicle was in a normal driving state.Experimental results showed that this method could detect abnormal behaviors of coal mine vehicles by using the location，speed and direction of coal mine vehicles，and had high applicability. |
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| Keywords: | ,infrared remote sensing information, coal mine vehicles, abnormal behavior, detection methods |
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