红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2009年
6期
1099-1103
,共5页
道路中线%激光雷达%多尺度
道路中線%激光雷達%多呎度
도로중선%격광뢰체%다척도
Road centerlines%LIDAR%Multi-scale
机载激光雷达(LIDAR)技术的出现为道路特征的获取提供了新的途径.在分析现有道路提取现状的基础上,针对激光雷达数据的特点以及单一尺度下道路中线提取方法的不足,提出一种基于多尺度追踪的道路中线提取方法.该方法首先采用逐步约束的方法进行道路激光点的提取,包括高程约束、强度约束以及区域点密度和区域面积的约束等;然后基于道路点云生成的不同尺度距离影像的形态学细化结果,采用多尺度追踪的方法实现道路中线的提取,其中多尺度追踪方法由大尺度道路中线的迭代追踪以及小尺度道路中线的启发式追踪两部分组成.最后采用实地数据进行验证,结果表明:该方法能有效地从LIDAR点云中提取道路中线信息,并具有较好的精度.
機載激光雷達(LIDAR)技術的齣現為道路特徵的穫取提供瞭新的途徑.在分析現有道路提取現狀的基礎上,針對激光雷達數據的特點以及單一呎度下道路中線提取方法的不足,提齣一種基于多呎度追蹤的道路中線提取方法.該方法首先採用逐步約束的方法進行道路激光點的提取,包括高程約束、彊度約束以及區域點密度和區域麵積的約束等;然後基于道路點雲生成的不同呎度距離影像的形態學細化結果,採用多呎度追蹤的方法實現道路中線的提取,其中多呎度追蹤方法由大呎度道路中線的迭代追蹤以及小呎度道路中線的啟髮式追蹤兩部分組成.最後採用實地數據進行驗證,結果錶明:該方法能有效地從LIDAR點雲中提取道路中線信息,併具有較好的精度.
궤재격광뢰체(LIDAR)기술적출현위도로특정적획취제공료신적도경.재분석현유도로제취현상적기출상,침대격광뢰체수거적특점이급단일척도하도로중선제취방법적불족,제출일충기우다척도추종적도로중선제취방법.해방법수선채용축보약속적방법진행도로격광점적제취,포괄고정약속、강도약속이급구역점밀도화구역면적적약속등;연후기우도로점운생성적불동척도거리영상적형태학세화결과,채용다척도추종적방법실현도로중선적제취,기중다척도추종방법유대척도도로중선적질대추종이급소척도도로중선적계발식추종량부분조성.최후채용실지수거진행험증,결과표명:해방법능유효지종LIDAR점운중제취도로중선신식,병구유교호적정도.
The LIDAR technology provides a new approach for acquiring road information.Having analyzed characteristics of LIDAR datasets as well as deficiencies of current road extracting methods, a multi-scale tracing method was proposed to extract the road centerlines. Firstly, candidate road points were segmented from raw LIDAR points cloud by a series of constraint procedures including height-constraint, intensity-constraint, local point density and region area constraint, and so on. Secondly, based on morphological thinning results of multi-scale road range images generated from road points segmented above,road centedines were extracted by a multi-scale centerline tracing method, which consisted of two steps:an iterative tracing procedure on the large scale range image and a heuristics tracing procedure on the small one. Finally, the proposed method was validated by one LIDAR dataset with complex road networks. The result shows that the proposed method can extract road centerlines from LIDAR points cloud effectively and precisely.