摘要
为了解决高速铁路轨道表面缺陷机器视觉检测系统中采集图像的冗余问题,本文提出一种钢轨表面图像冗余信息的模糊匹配算法.该种算法首先采用竖直投影法提取钢轨表面区域;之后对钢轨表面区域进行预处理并二值化,得到缺陷的位置信息;然后通过感知哈希算法,得到钢轨表面缺陷的形态信息;最后计算缺陷的位置误差和形态相似度,基于模糊匹配算法,得到匹配结果.通过实验验证,该算法能有效识别系统图像中的冗余部分,准确率达到97.5%.
In order to address the redundancy of image in the detection process of rail surface defects,an algorithm of matching for the redundancies of rail surface images was proposed.At the beginning,the rail surface area was extracted by using the vertical projection method.And then,the location information of defects was obtained through the image preprocess and binarization on the rail surface.Next,the morphological information of the rail surface defects was achieved in the horizontal projection method.At last,the defect location information and morphological information were matched on the basis of the improved fuzzy matching algorithm.The experiment results verify that this algorithm can effectively identify the redundancy information of image,and the accuracy rate is as high as 97.5%.
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2016年第4期75-80,共6页
Journal of Hunan University:Natural Sciences
基金
国家自然科学基金重点资助项目(60835004)
国家高技术研究发展计划('863'计划)资助项目(2007AA04I244)~~
关键词
机器视觉
钢轨
表面缺陷
模糊匹配
machine vision
rail
surface defects
fuzzy matching
