Research on Detection Algorithm for Rail Fastener Based on Computer Vision

被引：0
|
作者：
Liu, Xin [1 ]
Wang, Hongbin [1 ]
Zhou, Bin [1 ]
机构：
[1] Lanzhou Inst Technol, Dept Elect & Informat Engn, Lanzhou 730050, Gansu, Peoples R China
来源：
PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC, CONTROL AND AUTOMATION ENGINEERING (MECAE 2018) | 2018年 / 149卷
关键词：
Computer Vision; Rail Fastener; HOG Features; Nearest Neighbor Classifier;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The traditional rail detection method cannot meet the demand of line repair, so a detection algorithm for rail fastener based on computer vision is proposed, which combines projection method and scanning of pixels in specific region to position the position of fastener, and adopts gray-scale features and HOG features to describe feature vector of fastener, then uses Chi square distance classifier to extract features. The experimental result shows the algorithm is effective and feasible to a certain extent.
引用
收藏
页码：647 / 652
页数：6
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