• DocumentCode
    463381
  • Title

    Geometric Primitives Detection in Aerial Image

  • Author

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

  • Author_Institution
    Graduate Sch. of IPS, Waseda Univ., Fukuoka
  • Volume
    1
  • fYear
    2006
  • fDate
    17-19 July 2006
  • Firstpage
    400
  • Lastpage
    404
  • Abstract
    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 corners 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
  • Keywords
    feature extraction; object detection; aerial image interpretation; geometric primitives detection; linear feature extraction; trichotomy line extraction; Detectors; Feature extraction; Image edge detection; Image resolution; Image segmentation; Labeling; Laboratories; National electric code; Pixel; Shape; Geometric primitive extraction; Line updating; Trichotomy line extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-0475-4
  • Type

    conf

  • DOI
    10.1109/COGINF.2006.365523
  • Filename
    4216440