{"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.