Xu Pengfei, Zhou Zhiqing, Geng Zexun
Department of Information Engineering, Pingdingshan University, Pingdingshan, 467000, Henan, China.
Faculty of Engineering, Built Environment & Information Technology, SEGI University, Kuala Lumpur, Malaysia.
Sci Rep. 2022 Oct 25;12(1):17899. doi: 10.1038/s41598-022-22564-8.
Coal is one of the main energy sources in China. The country attaches great importance to the development of coal mining industry, and coal production is on the rise. At the same time, mine safety accidents are becoming more and more frequent, and the country is paying more and more attention to mine safety accidents. The underground environment of coal mine is complex, noisy and uneven, and there will be problems such as occlusion and high false detection rate during video monitoring. In order to ensure the safety of underground personnel, moving target detection and tracking based on video monitoring information is of great significance for coal mine safety production. The purpose of this paper is to study how to analyze and study the monitoring of moving targets in coal mines based on computer vision processing, and describe the image processing methods. This paper puts forward the problem of target monitoring, which is based on image processing, and then elaborates on the concept of image enhancement and related algorithms. From the average gradient, the algorithm in this paper is 56.60% higher than the histogram equalization algorithm, and 68.26% higher than the dark primary color prior dehazing algorithm. and designs and analyzes cases of image enhancement in coal mines. The experimental results show that the information entropy of the algorithm in this paper is 31.10% higher than that of the dark primary color prior dehazing algorithm, and 18.72% higher than that of the histogram equalization algorithm. It can be seen that the algorithm in this paper can achieve better enhancement effect.
煤炭是中国主要能源之一。国家高度重视煤炭开采行业的发展，煤炭产量不断上升。与此同时，煤矿安全事故日益频繁，国家对煤矿安全事故也越来越重视。煤矿井下环境复杂、嘈杂且不平坦，视频监控时会出现遮挡和误检率高等问题。为确保井下人员安全，基于视频监控信息的运动目标检测与跟踪对煤矿安全生产具有重要意义。本文旨在研究如何基于计算机视觉处理对煤矿中的运动目标监测进行分析研究，并描述图像处理方法。本文提出基于图像处理的目标监测问题，接着阐述图像增强的概念及相关算法。从平均梯度来看，本文算法比直方图均衡化算法高56.60%，比暗原色先验去雾算法高68.26%。并设计和分析了煤矿图像增强案例。实验结果表明，本文算法的信息熵比暗原色先验去雾算法高31.10%，比直方图均衡化算法高18.72%。可见本文算法能取得较好的增强效果。
