Discovering Local Cooccurring Patterns From Aerial Images

Wenjing Jia, David Tien

Research output: Book chapter/Published conference paperConference paperpeer-review

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Developing a spatial searching engine to enhance the search capabilities of large spatial repositories for GIS update has attracted more and more attention. Existing methods are usually designed to extract limited types of objects and use only one aspect of features of images. In this paper, we propose to use the local cooccurring patterns to disclose the cooccurring relationships among each dominant local features and use this local cooccurring patterns to recognize an object from aerial images. For this purpose, we investigate three types of local features: colour-based features, texture-based features, and edge-based shape features. In order to facilitate the feature extraction procedure, we first use discontinuity-preserving smoothing methods to filter the input image. Two popular smoothing techniques are tested and compared. Experimental results are presented in this paper.
Original languageEnglish
Title of host publication4th ICITA 2007
EditorsShi Guanfan
Place of PublicationSydney, Australia
PublisherMacquarie Scientific Press
Number of pages6
ISBN (Electronic)9780980326703
Publication statusPublished - 2007
EventInternational Conference on Information Technology and Applications (ICITA) - Harbin, China, China
Duration: 15 Jan 200718 Jan 2007


ConferenceInternational Conference on Information Technology and Applications (ICITA)


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