  In photography, low depth of field (DOF) is an important technique to
emphasize the object of interest (OOI) within an image. Thus, low DOF images
are widely used in the application area of macro, portrait or sports
photography. When viewing a low DOF image, the viewer implicitly concentrates
on the regions that are sharper regions of the image and thus segments the
image into regions of interest and non regions of interest which has a major
impact on the perception of the image. Thus, a robust algorithm for the fully
automatic detection of the OOI in low DOF images provides 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
DOF 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 DOF images.
