• DocumentCode
    3259012
  • Title

    A Semi-Structured representation for Knowledge Discovering using Remote Sensing Images

  • Author

    Lopez-Ornelas, Erick ; Sedes, Florence

  • Author_Institution
    Univ. Autonoma Metropolitana-Unidad Cuajimalpa, Mexico
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    24
  • Lastpage
    28
  • Abstract
    In this paper we describe the basic functionalities of a system dedicated to process high-resolution satellite images and to handle them through (semi-) structured descriptors. These descriptors enable to manage in a unified representation two families of features extracted from the objects identified by image segmentation: the attributes characterizing each object, and the attributes characterizing relationships between objects. Our aim is to focus on the complementary of two approaches, on one hand concerns the remote sensing and the image segmentation, and on the other hand concerns the knowledge discovery and the modeling
  • Keywords
    data mining; feature extraction; image segmentation; remote sensing; feature extraction; high-resolution satellite images; image segmentation; knowledge discovery; remote sensing images; semistructured descriptors; semistructured representation; Availability; Data mining; Feature extraction; Image edge detection; Image segmentation; Morphology; Radiometry; Remote sensing; Satellite broadcasting; Spatial resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops, 2006. ICDM Workshops 2006. Sixth IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2702-7
  • Type

    conf

  • DOI
    10.1109/ICDMW.2006.21
  • Filename
    4063592