Geometric primitives detection in aerial image

Jing Wang*, Satoshi Goto, Kazuo Kunieda, Makoto Iwata, Hirokazu Koizumi, Hideo Shimazu, Takeshi Ikenaga


研究成果: Paper査読


Geometric Primitives are important features for aerial image interpretation, especially for understanding of manmade objects. With the increasing resolution of aerial image, growing size and complexity of image make it more difficult to efficiently extract dependable geometric features such as lines and corners. In this paper, we propose a novel linear feature extraction approach called 'Trichotomy line Extraction'. According to the knowledge of geometric properties of interested objects in aerial image, i.e. manmade objects, a rule is designed to remove line segments meaningless for boundaries of interested objects. Then line updating is carried out based on spatial and geometric relation between lines, to improve connectivity of boundary lines and also to extract comers on object boundary. Experiment results show that proposed line extraction method can perform efficiently with accurate linear features of objects in large aerial image and meaningless line segments removing process is effective to improve the geometric features' description of object and to reduce computing burden of following step.

出版ステータスPublished - 2006 12月 1
イベント5th IEEE International Conference on Cognitive Informatics, ICCI 2006 - Beijing, China
継続期間: 2006 7月 172006 7月 19


Conference5th IEEE International Conference on Cognitive Informatics, ICCI 2006

ASJC Scopus subject areas

  • 人工知能
  • 情報システム


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