Applying local cooccurring patterns for object detection from aerial images

Wenjing Jia, David Tien, Xiangjian He, Brian A. Hope, Qiang Wu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


Developing a spatial searching tool to enhance the search car pabilities of large spatial repositories for Geographical Information System (GIS) update has attracted more and more attention. Typically, objects to be detected are represented by many local features or local parts. Testing images are processed by extracting local features which are then matched with the object's model image. Most existing work that uses local features assumes that each of the local features is independent to each other. However, in many cases, this is not true. In this paper, a method of applying the local cooccurring patterns to disclose the cooccurring relationships between local features for object detection is presented. Features including colour features and edge-based shape features of the interested object are collected. To reveal the cooccurring patterns among multiple local features, a colour cooccurrence histogram is constructed and used to search objects of interest from target images. The method is demonstrated in detecting swimming pools from aerial images. Our experimental results show the feasibility of using this method for effectively reducing the labour work in finding man-made objects of interest from aerial images.

Original languageEnglish
Title of host publicationAdvances in Visual Information Systems - 9th International Conference, VISUAL 2007, Revised Selected Papers
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783540764137
Publication statusPublished - 2007
Externally publishedYes
Event9th International Conference on Visual Information Systems, VISUAL 2007 - Shanghai, China
Duration: 28 Jun 200729 Jun 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4781 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Visual Information Systems, VISUAL 2007


  • Colour cooccurrence histogram
  • Local cooccurring patterns
  • Swimming pool detection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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