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基于图像处理的轨旁组合信号灯识别方法 被引量:2

Recognition Method of the Combined Trackside Signal Light Based on Image Processing
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摘要 对列车轨旁信号灯进行准确辨识是保障列车安全运行的重要措施。然而,对于轨道系统而言,除了通常的单色信号灯外,还有组合(两种颜色)信号灯的指示方式。针对轨旁组合信号灯的识别问题,文中提出了一种基于图像处理技术对位于列车前方150 m内的轨旁组合信号灯的识别方法。根据组合信号灯的颜色和形状特征,采用颜色分割、形态学处理、霍夫变换等手段提取组合信号灯的候选区域。同时利用组合信号灯位于当前轨道右侧的位置特征以及组合信号灯之间圆心距的距离特征,定位其位置并识别组合灯颜色。实验结果表明,该方法能准确定位和识别轨旁组合信号灯,对绿与黄、两绿和两黄这3种组合灯的识别率分别为94.14%、96.21%、86.67%。 The trackside signal light is an important guidance for a running train in a rail transportation system.However,the combined trackside signal light included two colors is also used as a specific sign in addition to the usual single color signal light.In order to solve the recognition problem of the combined trackside signal light,a method based on image processing technology is employed to recognize the combined trackside signal light located within 150 m in front of train.As a result,the candidate region characteristics of the combined trackside signal light are extracted by color segmentation,morphological processing,and Hough transform.On the other hand,the combined trackside signal light can be positioned on the right of running rail train.The central spacing between two single lights can determine whether or not existing combined trackside signal light to remove the possible interferences from other lights or environment.The experimental results indicate that this method can accurately locate and recognize the combined trackside signal light,and the color correction ratio is 94.14%for green and yellow light,96.21%for two green lights,86.67%for two yellow lights.
作者 郭齐成 沈拓 张轩雄 GUO Qicheng;SHEN Tuo;ZHANG Xuanxiong(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety,Tongji University,Shanghai 201804,China)
出处 《电子科技》 2023年第7期8-15,共8页 Electronic Science and Technology
基金 国家自然科学基金(U1734211)。
关键词 轨旁组合信号灯 图像处理 颜色分割 形态学操作 霍夫变换 边缘检测 轨道提取 图像识别 combined trackside signal light image processing color segmentation morphological operation Hough transform edge detection track extraction image recognition
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