Carlos Cabo, S. Garcia-Cortes, A. Menéndez-Díaz, C. Ordóñez
{"title":"Automatic road edge detection from Mobile Laser Scanning (MLS)","authors":"Carlos Cabo, S. Garcia-Cortes, A. Menéndez-Díaz, C. Ordóñez","doi":"10.1117/12.2257108","DOIUrl":null,"url":null,"abstract":"In this article we present an algorithm for automatic road edge detection from MLS (Mobile Laser Scanning) data. The method takes advantage of linear structures derived from MLS point clouds. These lines are extracted from the point cloud and grouped following geometric restrictions. Then, the outlines of the groups are extracted as road edges. Finally, a moving window filter is applied to those points in order to remove outliers and delineate the road edge. The method was tested on an 800m stretch of road, and the results were checked through visual inspection. Correctness and completeness were 99.1% and 97.5%, respectively.","PeriodicalId":112965,"journal":{"name":"Optical Angular Momentum","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Angular Momentum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2257108","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
In this article we present an algorithm for automatic road edge detection from MLS (Mobile Laser Scanning) data. The method takes advantage of linear structures derived from MLS point clouds. These lines are extracted from the point cloud and grouped following geometric restrictions. Then, the outlines of the groups are extracted as road edges. Finally, a moving window filter is applied to those points in order to remove outliers and delineate the road edge. The method was tested on an 800m stretch of road, and the results were checked through visual inspection. Correctness and completeness were 99.1% and 97.5%, respectively.