华东交通大学学报2017，Vol.34Issue(2)：72-77,6.
基于计算机视觉的钢轨扣件检测算法研究
Research of Detection Algorithm for Rail Fastening Based on Computer Vision
摘要
Abstract
As the traditional rail detection method can no longer meet the railway maintenance requirements, an detection algorithm of rail fastening based on computer vision is proposed in this paper. The position of the fas-tener can be located by using the projection method and the method of scanning pixels and statistics of specific areas. The characteristics of fasteners are described by way of gray level features and HOG features, and the Chi square distance classifier is adopted to extract features. Results indicate that the algorithm shows certain validity and feasibility.关键词
计算机视觉/钢轨扣件/HOG特征/最近邻分类器Key words
computer vision/rail fastening/HOG features/K-nearest neighbor classifier分类
交通工程引用本文复制引用
刘馨,穆颖,张斌..基于计算机视觉的钢轨扣件检测算法研究[J].华东交通大学学报,2017,34(2):72-77,6.基金项目
国家自然基金项目(61461023) （61461023）
甘肃省教育厅高等学校第二批科研项目(2013B-096) （2013B-096）
兰州工业学院青年科技创新项目(15K-009) （15K-009）
