【作者】 超木日力格；

【导师】 赵守国；

【作者基本信息】 北京交通大学 ， 模式识别与智能系统， 2012， 硕士

【摘要】 铁路运输在我国交通运输领域一直都占主导地位,在经济社会发展中具有特殊重要的作用。近年来,随着铁路的大面积提速调图,使得铁路的行车安全问题显得更加突出。尤其是,我国将长期以来一直实施的正、副司机操纵列车模式改为单司机值乘模式后,司机很难同时兼顾行车信号确认、列车的操纵及路面状况的瞭望等。针对这种现状,本文提出了机车司机视野扩展系统的框架及设计方案。虽然目前已有一些成熟的智能公路交通技术可以直接使用于铁路交通领域,但铁路智能监控视频有其自身突出的特点：铁路轨道部分有枕木、碎石道砟,不似公路路面那么干净；背景复杂,且在行车过程当中随时会改变等。本系统旨在通过利用铁路路轨特点实时的分析火车视频监控图像序列,检测、跟踪并分析威胁火车安全行驶的路障目标,达到减少事故发生率、提高铁路运输安全的目的。系统整体设计思路是将铁路静态路轨障碍物的检测和智能视频监控序列中动态障碍物的检测、跟踪相分开来。对于静态路轨障碍物的检测,主要运用了特征提取和特征匹配的算法。该算法将铁路障碍物的检测范围限制在图像铁轨部分,对检测窗内图像的纹理和灰度特征进行分析,从而判定障碍物的存在与否。而动态障碍物的检测是通过对运动目标的提取、运动目标的跟踪和目标的运动轨迹分析等部分展开。用光流背景建模方法提取运动目标,而后用Kalman+Mean shift算法对其进行实时跟踪,在跟踪的过程当中分析目标的运动轨迹。论文按系统框架、算法设计及系统仿真的顺序对机车司机视野扩展系统进行详细介绍。首先,提出机车司机视野扩展系统的总体设计方案和框架；而后,对系统算法原理进行阐述；最后,用仿真环境下采集的视频图像序列和图片对算法进行测试。实验结果表明,本系统的运行速度较快且抗噪能力较强,有一定的实用价值。更多还原

【Abstract】 Railway transport is the most widely used transportation method in China. Focusing on the increasing number of the railway passengers, the Ministry of Railways has been improving the speed of train for six times. High-speed train runs at much faster speeds than traditional train, so the traditional detection method with human-vision is not suitable for road surface condition observation of the high-speed train under the Single-Driver Duty mode. In order to deal with these problems, people begin to develop automatic monitoring system to replace the human to complete these work.Although there are some mature intelligent video surveillance systems can be used directly in the field of railway transport, railway intelligent surveillance video has its own characteristics such as railway is not as clean as the road surface cause of the railway sleepers and ballast. Therefore, this paper describes development of the locomotive driver’s vision expansion system.The system consists of two parts:movable obstacle detection and static obstacle detection. The static roadblock detection algorithm improves the detection speed by limiting the scope of detection in the tracks area. After sets up the Obstacle detection window, searches the roadblock target by analyzing texture feature and gray feature of the picture within the detection window. The most important part of movable roadblock detection is target tracking. Firstly, use the Inter-frame Difference algorithm to extract the moving region; secondly, eliminate the moving background pixels by establishing optical flow background model and get foreground objects; thirdly, track these objects and record the motion curve; finally, analyze the motion curve.After making sure the existence of dangerous obstacles, send alerts to driver. The development of system is aimed at reduce accidents and improve railway transport safety by detect, track and analyze the roadblock target in the real-time video surveillance image sequence of train. The experiments show that this study has practical value in detect、track and analyze roadblock object.更多还原