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轨道交通线路净空安全是确保列车平稳、不间断运行的基础.由于轨间异物对行车安全产生严重影响，所以基于非轨道电路的轨道异物入侵检测系统在铁路系统中具有十分广泛的应用前景.本文提出了一种基于移动车载摄像机检测轨间异物的方法.首先，通过钢轨识别算法自动定位钢轨位置，并确定列车前方轨道是否有其它列车或公路车辆等大型异物，若有则进行报警；之后，基于边缘检测的异物检测算法自动检测轨间可疑小异物，同时提取可疑异物的尺度信息和颜色索引参数等相关特征；最后，用支持向量机（SVM）来对可疑小异物区域进行分类和辨识.车载实验结果表明，该方法可以有效地检测出轨间异物.

Railway Obstacle Detection using Onboard Forward-Viewing Camera

Track clearance is the foundation of the safe and continuous operation of railway system.Non-track circuit-based intrusion and obstacle detection techniques may be well applied for railway systems because the rail obstacles always greatly reduced the train speed.In this paper,a machine vision-based obstacle detection method is proposed based on the onboard forward-viewing camera and real-time image processing algorithms.First,a rail recognition algorithm is developed to automatically locate the rails in front of the train and find whether the obstacles in track segment are large enough to block the whole track ahead,such as,rail or road vehicles.Then,a small obstacle detection algorithm based on edge detection is used to detect the candidate obstacle areas.Typical features of the obstacle areas,such as dimension and color index parameters,are thus obtained.Finally,a support vector machine(SVM) is trained to classify the candidate obstacle areas and verify the true obstacles.Experiments show that the proposed method can effectively detect obstacles.