Shadow-Based Rooftop Segmentation in Visible Band Images

John Femiani, Er Li, Anshuman Razdan, Peter Wonka

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


This paper presents a method to extract rooftops from aerial images with only visible red, green, and blue bands of data. In particular, it does not require near-infrared data, lidar, or multiple viewpoints. The proposed method uses shadows in the image in order to detect buildings and to determine a set of constraints on which parts can or cannot be rooftops. We then use the grabcut algorithm to identify complete rooftop regions and a method to make corrections that simulate a user performing interactive image segmentation in order to improve the precision of our results. The precision, recall, and F-score of the proposed approach show significant improvement over two very recently published papers. On our test dataset, we observe an average F-score of 89% compared to scores of 68% and 33%.

Original languageEnglish (US)
Article number6981919
Pages (from-to)2063-2077
Number of pages15
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Issue number5
StatePublished - May 1 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.


  • Buildings
  • rooftops detectors
  • shadows
  • urban areas

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science


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