会议论文详细信息
4th International Conference on Advanced Engineering and Technology
An Aggregated Method for Determining Railway Defects and Obstacle Parameters
Loktev, Daniil^1 ; Loktev, Alexey^2 ; Stepanov, Roman^1 ; Pevzner, Viktor^3 ; Alenov, Kanat^4
Department of Structural and Theoretical Mechanics, National Research Moscow State Construction University, Moscow
129337, Russia^1
Department of Transport Construction, Russian University of Transport, Moscow
125190, Russia^2
Department Complex Issues of Traffic Safety, VNIIZHT, Moscow
129626, Russia^3
Kyzylorda State University M.Korkyt Ata, Kyzylorda
120014, Kazakhstan^4
关键词: Best approximations;    Direction of movements;    Focal lengths;    Moving objects;    Physical effects;    Statistical approach;    Stereoscopic vision;    Video detector;   
Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/317/1/012021/pdf
DOI  :  10.1088/1757-899X/317/1/012021
来源: IOP
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【 摘 要 】

The method of combining algorithms of image blur analysis and stereo vision to determine the distance to objects (including external defects of railway tracks) and the speed of moving objects-obstacles is proposed. To estimate the deviation of the distance depending on the blur a statistical approach, logarithmic, exponential and linear standard functions are used. The statistical approach includes a method of estimating least squares and the method of least modules. The accuracy of determining the distance to the object, its speed and direction of movement is obtained. The paper develops a method of determining distances to objects by analyzing a series of images and assessment of depth using defocusing using its aggregation with stereoscopic vision. This method is based on a physical effect of dependence on the determined distance to the object on the obtained image from the focal length or aperture of the lens. In the calculation of the blur spot diameter it is assumed that blur occurs at the point equally in all directions. According to the proposed approach, it is possible to determine the distance to the studied object and its blur by analyzing a series of images obtained using the video detector with different settings. The article proposes and scientifically substantiates new and improved existing methods for detecting the parameters of static and moving objects of control, and also compares the results of the use of various methods and the results of experiments. It is shown that the aggregate method gives the best approximation to the real distances.

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