Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (21): 242-247.DOI: 10.3778/j.issn.1002-8331.1908-0189

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Dangerous Tree Detecting Based on Longitudinal Parallax

FAN Yuping, TANG Quanhua, HUANG Longjun   

  1. School of Software, Jiangxi Normal University, Nanchang 330022, China
  • Online:2020-11-01 Published:2020-11-03



  1. 江西师范大学 软件学院,南昌 330022


As trees intrude intoorbits area threaten security of railway transportation, it is necessary to identify and detect invasive trees. Adangerous tree detecting method based on longitudinal parallax is proposed to determine the location relationship between trees and orbits. Multi-scale threshold segmentation is performed on the image using multiple colors. The tree regions are recognized by color feature and fractal dimension. The distances between the tree areas and the center of the view plane are calculated by region matching and moving of two frames. The catenary brackets are detected and measured to optimize the distance estimation of tree areas. Experimental results show that the detection efficiency and measurement accuracy based on longitudinal parallax can meet the needs of real-time detection of railway dangerous trees.

Key words: dangerous tree detecting, tree recognition, image distance measurement, longitudinal parallax



关键词: 危树检测, 树木识别, 图像测距, 纵向视差