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Joint horizontal-vertical enhancement and tracking scheme for robust contact-point detection from pantograph-catenary infrared images

机译:Pantography红外图像强稳压接触点检测的联合水平垂直增强和跟踪方案

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摘要

It is a key point to accurately and stably detect the pantograph-catenary contact point for its geometric parameter measurement from infrared images under complex backgrounds (e.g., cloud, cross-bridge, curved contact wire, in particular, the contact wire switching time). In order to complete the task of accurate and robust contact point detection, this paper proposes an progressive detection strategy, called as joint horizontal-vertical enhancement and tracking (JHVET), including three crucial parts: Firstly, an input infrared image is decomposed into a horizontal image layer and a vertical image layer by a horizontal-vertical enhancement operator, and the potential contact point is located by an extensive random sample consensus (RANSAC) algorithm. Secondly, an updated tracking approach is proposed to deal with the contact point detection problem in the contact wire switching time. Finally, an initial scheme is proposed to determine the first contact wire after switching the contact wire. Experimental results verify the effectiveness of the proposed JHVET method in both quantization and qualification. Especially, the performance with high detection accuracy (98.23%), low average pixel error (0.523 pixel), and satisfactory detection rate (over 108 fps) yielded by the proposed JHVET method is very suitable for its extensive application.
机译:它是从复杂背景下的红外图像(例如,云,交叉桥,弯曲的接触线,特别是接触线切换时间)的红外图像精确且稳定地检测其几何参数测量的接触诱变型接触点的关键点。为了完成准确且坚固的接触点检测的任务,本文提出了一种渐进的检测策略,称为关节水平 - 垂直增强和跟踪(JHVET),包括三个关键部分:首先,输入红外图像被分解成一个水平图像层和垂直图像层由水平垂直增强算子,潜在的接触点位于广泛的随机样本共识(RANSAC)算法。其次,提出了更新的跟踪方法来处理接触线切换时间中的接触点检测问题。最后,提出了一种初始方案来在切换接触线之后确定第一接触线。实验结果验证了所提出的JHVET方法在量化和资格中的有效性。特别是,所提出的JHVET方法产生的高检测精度(98.23%),低平均像素误差(0.523像素)和令人满意的检测率(超过108fps)的性能非常适合其广泛的应用。

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