Road boundary extraction using shadow path reconstruction in urban areas

Kong Hyun Yun, Hong Gyoo Sohn, Joon Heo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


High-resolution aerial color image offers great possibilities for geometric and semantic information for spatial data generation. However, shadow casts by buildings and trees in high-density urban areas obscure much of the information in the image giving rise to potentially inaccurate classification and inexact feature extraction. Though many researches have been implemented for solving shadow casts, few studies have been carried out about the extraction of features hindered by shadows from aerial color images in urban areas. This paper presents a road boundary extraction technique that combines information from aerial color image and Light Detection And Ranging (LIDAR) data. The following steps have been performed to remove shadow effects and to extract road boundary from the image. First, the shadow regions of the aerial color image are precisely located using LIDAR DSM (Digital Surface Model) and solar positions. Second, shadow regions assumed as road are corrected by shadowpath reconstruction algorithms. After that, road boundary extraction is implemented by segmentation, edge detection, and edge linking method. Finally, road boundary lines are extracted as vector data by vectorization technique. The experimental results show that this approach is effective and great potential advantages.

Original languageEnglish
Title of host publicationComputational Science and Its Applications - ICCSA 2006
Subtitle of host publicationInternational Conference, Proceedings - Part II
PublisherSpringer Verlag
Number of pages7
ISBN (Print)3540340726, 9783540340720
Publication statusPublished - 2006
EventICCSA 2006: International Conference on Computational Science and Its Applications - Glasgow, United Kingdom
Duration: 2006 May 82006 May 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3981 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherICCSA 2006: International Conference on Computational Science and Its Applications
Country/TerritoryUnited Kingdom

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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