Improved Harris feature point set for orientation-sensitive urban-area detection in aerial images

Andrea Kovács, Tamás Szirányi

Research output: Contribution to journalArticle

41 Citations (Scopus)


This letter addresses the automatic detection of urban area in remotely sensed images. As manual administration is time consuming and unfeasible, researchers have to focus on automated processing techniques, which can handle various image characteristics and huge amount of data. The applied method extracts feature points in the first step, which is followed by the construction of a voting map to represent urban areas. Finally, an adaptive decision making is performed to find urban areas. This letter presents methodological contributions in two key issues to the algorithm: 1) An automatically extracted Harris-based feature point set is introduced for the first step, which is able to represent urban areas more precisely. 2) An improved orientation-sensitive voting technique is proposed, exploiting the orientation information calculated in the local neighborhood of points. Evaluation results show that the proposed contributions increase the detection accuracy of urban areas.

Original languageEnglish
Pages (from-to)796-800
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Issue number4
Publication statusPublished - Jul 1 2013



  • Aerial images
  • Modified Harris detector
  • Orientation sensitivity
  • Spatial voting
  • Urban-area detection

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering

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