• DocumentCode
    1743083
  • Title

    Statistical shape features in content-based image retrieval

  • Author

    Brandt, Sami ; Laaksonen, Jorma ; Oja, Erkki

  • Author_Institution
    Lab. of Comput. Eng., Helsinki Univ. of Technol., Espoo, Finland
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1062
  • Abstract
    In this article the use of shape features in content-based image retrieval is studied. The emphasis is on techniques which do not demand object segmentation. PicSOM, the image retrieval system used in the experiments, requires that features are represented by constant-sized feature vectors for which the Euclidean distance can be used as a similarity measure. The shape features suggested here are edge histograms and Fourier transform based features computed for an edge image in Cartesian and polar coordinate planes. The results show that both local and global shape features are important clues of shapes in an image
  • Keywords
    Fourier transforms; edge detection; feature extraction; image retrieval; search engines; statistical analysis; visual databases; Euclidean distance; Fourier transform; PicSOM; content-based image retrieval; edge detection; edge histograms; feature vectors; image database; search engine; statistical shape features; Content based retrieval; Feature extraction; Histograms; Image databases; Image retrieval; Image segmentation; Laboratories; Search engines; Shape; Spatial databases;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.906258
  • Filename
    906258