• DocumentCode
    2825740
  • Title

    Robust segmentation of relevant regions in low depth of field images

  • Author

    Graf, Franz ; Kriegel, Hans-Peter ; Weiler, Michael

  • Author_Institution
    Ludwig-Maximilians-Univ. Munchen, Munich, Germany
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    2861
  • Lastpage
    2864
  • Abstract
    Low depth of field (DOF) is an important technique to emphasize the object of interest (OOI) within an image. When viewing a low depth of field image, the viewer implicitly segments the image into region of interest and non regions of interest which has major impact on the perception of the image. Thus, robust algorithms for the detection of the OOI in low DOF images provide valuable information for subsequent image processing and image retrieval. In this paper we propose a robust and parameterless algorithm for the fully automatic segmentation of low depth of field images. We compare our method with three similar methods and show the superior robustness even though our algorithm does not require any parameters to be set by hand. The experiments are conducted on a real world data set with high and low depth of field images.
  • Keywords
    image retrieval; image segmentation; DOF; OOI; field images; fully automatic segmentation; image processing; image retrieval; image segmentation; low depth of field; nornregions of interest; object of interest; parameterless algorithm; region of interest; relevant regions; robust algorithms; robust segmentation; Approximation methods; Conferences; Image color analysis; Image segmentation; Robustness; Signal processing algorithms; Image Segmentation; Low Depth of Field; Object of Interest;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2011 18th IEEE International Conference on
  • Conference_Location
    Brussels
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4577-1304-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2011.6116145
  • Filename
    6116145