• DocumentCode
    3205392
  • Title

    Shadow identification

  • Author

    Jiang, Caixia ; Ward, Matthew O.

  • Author_Institution
    Worcester Polytech. Inst., MA, USA
  • fYear
    1992
  • fDate
    15-18 Jun 1992
  • Firstpage
    606
  • Lastpage
    612
  • Abstract
    A shadow identification and classification method for real images is developed. The method is based on extensive analysis of shadow intensity and shadow geometry. The procedure for identifying shadows is divided into low-level, middle-level, and high-level processes. The low-level extracts dark regions from images. The middle-level process performs feature analysis on dark regions, including detecting vertices on the outlines of dark regions, identifying penumbrae in dark regions, assigning the subregions in dark regions as self-shadows and cast shadows, and finding object regions adjacent to dark regions. The high-level process integrates the information derived from the previous processes and confirms shadows among the dark regions
  • Keywords
    image segmentation; pattern recognition; cast shadows; dark regions; detecting vertices; feature analysis; high-level process; real images; self-shadows; shadow classification; shadow geometry; shadow identification; shadow intensity; Clouds; Geometry; Histograms; Humans; Layout; Light sources; Object detection; Performance analysis; Shape; Surface texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
  • Conference_Location
    Champaign, IL
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2855-3
  • Type

    conf

  • DOI
    10.1109/CVPR.1992.223128
  • Filename
    223128