Traffic lights detection and recognition based on color segmentation and circle hough transform

D. H. Widyantoro, K. I. Saputra
{"title":"Traffic lights detection and recognition based on color segmentation and circle hough transform","authors":"D. H. Widyantoro, K. I. Saputra","doi":"10.1109/ICODSE.2015.7437004","DOIUrl":null,"url":null,"abstract":"Automatic detection and recognition of traffic light system is a useful real world application. In this paper, we describe our effort in building such a system. The image of scene obtained from on-vehicle camera is first segmented and converted into three binary images representing images with red, green and yellow color, respectively. Each binary image is then smoothed using Gaussian filter in order to remove noise. The traffic light is detected by finding circular object on the smoothed binary images. We employ Circle Hough transform for circular object detection. The recognition of traffic light is based on the color represented by the binary image with detected circular object. Evaluation of the above method with two real traffic videos demonstrates the effectiveness of the method.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"55 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Data and Software Engineering (ICoDSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICODSE.2015.7437004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

Abstract

Automatic detection and recognition of traffic light system is a useful real world application. In this paper, we describe our effort in building such a system. The image of scene obtained from on-vehicle camera is first segmented and converted into three binary images representing images with red, green and yellow color, respectively. Each binary image is then smoothed using Gaussian filter in order to remove noise. The traffic light is detected by finding circular object on the smoothed binary images. We employ Circle Hough transform for circular object detection. The recognition of traffic light is based on the color represented by the binary image with detected circular object. Evaluation of the above method with two real traffic videos demonstrates the effectiveness of the method.
基于颜色分割和圆霍夫变换的交通灯检测与识别
红绿灯自动检测与识别系统是一个非常有用的现实应用。在本文中,我们描述了我们在构建这样一个系统方面所做的努力。首先对车载摄像机获取的场景图像进行分割,并将其转换为三幅二值图像,分别代表红、绿、黄三种颜色的图像。然后使用高斯滤波器对每个二值图像进行平滑,以去除噪声。通过在光滑的二值图像上寻找圆形物体来检测红绿灯。采用圆霍夫变换对圆形目标进行检测。交通灯的识别是基于检测到的圆形物体的二值图像所表示的颜色。用两个真实的交通视频对该方法进行了评价,验证了该方法的有效性。
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 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:604180095
Book学术官方微信