{"title":"Road Detection Method Corresponded to Multi Road Types with Flood Fill and Vehicle Control","authors":"Tomoya Fukukawa, Yu Maeda, K. Sekiyama, T. Fukuda","doi":"10.1109/RVSP.2013.68","DOIUrl":null,"url":null,"abstract":"This paper proposes the road detection method corresponded to multi road types with Flood Fill. Flood Fill is one of the image processing methods to partition the region of input image based on RGB color model. Road detection is useful for automatic robots because the robots work on various road surface in outdoor environment. The proposed method has two features. Firstly, the method can cancel the influence of shadow on road by using HSV color model. Secondly, the method can recognize multi road types by k-nearest neighbor algorithm. By using the proposed method, the robot can select the suitable controller for road surface or the safety route. We implement the proposed method in vehicle navigation and the availability is verified by the experimental results.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"23 1","pages":"274-277"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Second International Conference on Robot, Vision and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RVSP.2013.68","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper proposes the road detection method corresponded to multi road types with Flood Fill. Flood Fill is one of the image processing methods to partition the region of input image based on RGB color model. Road detection is useful for automatic robots because the robots work on various road surface in outdoor environment. The proposed method has two features. Firstly, the method can cancel the influence of shadow on road by using HSV color model. Secondly, the method can recognize multi road types by k-nearest neighbor algorithm. By using the proposed method, the robot can select the suitable controller for road surface or the safety route. We implement the proposed method in vehicle navigation and the availability is verified by the experimental results.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
