Spatial Feature Based Shadow Detection in Visual Traffic Surveillance System

Shaohua Xu, Yong Zhao, Chunyu Yu, Ling Shen
{"title":"Spatial Feature Based Shadow Detection in Visual Traffic Surveillance System","authors":"Shaohua Xu, Yong Zhao, Chunyu Yu, Ling Shen","doi":"10.1109/CCCM.2008.55","DOIUrl":null,"url":null,"abstract":"A shadow detection algorithm base on spatial features was proposed, in the case of focusing on traffic vehicle detection system. First of all, multi-foreground rectangles were extracted by using Gaussian mixture model (GMM) and edge detection operator of mathematical morphology. Then, histogram of horizontal location - foreground point number of vertical direction was computed, combined with optimum threshold segmentation, shadow areas were removed. To enhance the adaptability, the system learns direction relations between target and its shadow, automatically. Results were presented for several video sequences representing a variety of illumination conditions. Experimental results in different traffic conditions showed our technique robust, self-adaptive, and real-time.","PeriodicalId":326534,"journal":{"name":"2008 ISECS International Colloquium on Computing, Communication, Control, and Management","volume":"19 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 ISECS International Colloquium on Computing, Communication, Control, and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCCM.2008.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

A shadow detection algorithm base on spatial features was proposed, in the case of focusing on traffic vehicle detection system. First of all, multi-foreground rectangles were extracted by using Gaussian mixture model (GMM) and edge detection operator of mathematical morphology. Then, histogram of horizontal location - foreground point number of vertical direction was computed, combined with optimum threshold segmentation, shadow areas were removed. To enhance the adaptability, the system learns direction relations between target and its shadow, automatically. Results were presented for several video sequences representing a variety of illumination conditions. Experimental results in different traffic conditions showed our technique robust, self-adaptive, and real-time.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于空间特征的视觉交通监控系统阴影检测
针对交通车辆检测系统,提出了一种基于空间特征的阴影检测算法。首先,利用高斯混合模型(GMM)和数学形态学边缘检测算子提取多个前景矩形;然后,计算水平位置-垂直方向前景点个数直方图,结合最优阈值分割,去除阴影区域;为了增强自适应能力,系统自动学习目标与阴影之间的方向关系。给出了代表各种光照条件的几个视频序列的结果。在不同交通条件下的实验结果表明,该技术具有鲁棒性、自适应性和实时性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Design and Analyze the Model of the Management System Based on Active Network Dynamic Test and Evaluating System for Flight Control System Analyzing the Impact of Organizational Constraints on Performance of E-Business: A Research Perspective D-Stable H8 Fault-Tolerant Control for Delta Operator Systems with Actuator Failure The Logistic Management for E-Commerce
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1