Tunnel moving target detection based on local structure of image and gray scale information

Haiyang Yu, Yawen Hu, Hongyu Guo, Lin Fang
{"title":"Tunnel moving target detection based on local structure of image and gray scale information","authors":"Haiyang Yu, Yawen Hu, Hongyu Guo, Lin Fang","doi":"10.1109/ICITE.2016.7581316","DOIUrl":null,"url":null,"abstract":"Tunnel moving target detection is subject to the influence of light condition and motion blur, the traditional motion detection method based on pixel points can not be very good at segmenting moving target. To solve this problem, frame difference detection method based on local structure of image and gray level information is proposed. The local mean difference information of the image is calculated by the improved algorithm, and then the similarity measure function and the gray scale measure function are constructed. The similarity measure function effectively describes the structural features of moving objects, and reduces the influence of image background information. The gray scale function is better to highlight the contrast of the target brightness, to increase the division of the target area and the background parts, and to realize the moving target detection correctly. The experimental results show that the detection method of the fusion structure and the gray level information can effectively segment the moving object.","PeriodicalId":352958,"journal":{"name":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITE.2016.7581316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Tunnel moving target detection is subject to the influence of light condition and motion blur, the traditional motion detection method based on pixel points can not be very good at segmenting moving target. To solve this problem, frame difference detection method based on local structure of image and gray level information is proposed. The local mean difference information of the image is calculated by the improved algorithm, and then the similarity measure function and the gray scale measure function are constructed. The similarity measure function effectively describes the structural features of moving objects, and reduces the influence of image background information. The gray scale function is better to highlight the contrast of the target brightness, to increase the division of the target area and the background parts, and to realize the moving target detection correctly. The experimental results show that the detection method of the fusion structure and the gray level information can effectively segment the moving object.
基于图像局部结构和灰度信息的隧道运动目标检测
隧道运动目标检测受光照条件和运动模糊的影响,传统的基于像素点的运动检测方法不能很好地分割运动目标。为了解决这一问题,提出了基于图像局部结构和灰度信息的帧差检测方法。利用改进算法计算图像的局部均值差信息,构造相似度度量函数和灰度度量函数。相似性度量函数有效地描述了运动物体的结构特征,减少了图像背景信息的影响。灰度函数较好地突出了目标亮度的对比度,增加了目标区域与背景部分的分割,实现了对运动目标的正确检测。实验结果表明,融合结构和灰度信息的检测方法可以有效地分割运动目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信