• DocumentCode
    1870851
  • Title

    Efficient computation of objects´ spatial relations in digital images

  • Author

    Shabani, A.-H. ; Matsakis, P.

  • Author_Institution
    Univ. of Waterloo, Waterloo, ON, Canada
  • fYear
    2012
  • fDate
    April 29 2012-May 2 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Both quantitative and qualitative measures of directional spatial relationships (e.g., left, right, above) between two raster objects in a digital image are important for high-level computer vision tasks such as scene analysis and robot navigation. The histogram of forces can provide such measures, but cannot be computed in real-time. A new approach for real-time computation, based on a vector representation of raster objects, is presented. The performance of the proposed approach is examined in an extensive experiment. Considering processing time and accuracy, optimal assessments of directional spatial relationships for use in real-time applications can be obtained.
  • Keywords
    computer vision; image representation; statistics; digital images; force histogram; high-level computer vision tasks; object spatial relation computation; raster object vector representation; robot navigation; scene analysis; Accuracy; Force; Histograms; Indexes; Partitioning algorithms; Real-time systems; Vectors; Directional spatial relationships; Multiple Rectangle Representation (MRR) of an object; force histograms; relative position linguistic descriptions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Computer Engineering (CCECE), 2012 25th IEEE Canadian Conference on
  • Conference_Location
    Montreal, QC
  • ISSN
    0840-7789
  • Print_ISBN
    978-1-4673-1431-2
  • Electronic_ISBN
    0840-7789
  • Type

    conf

  • DOI
    10.1109/CCECE.2012.6335023
  • Filename
    6335023