Segmentation of heterogeneous document images : an ... - Tel

(a) Document image (b) Small Gabor kernel (c) Large Gabor kernel
tel-00912566, version 1 - 2 Dec 2013
Figure 4.7: Results of applying two Gabor filters with different kernel sizes to a
document image. This clearly shows the ability of Gabor filters to capture text lines
of different font sizes. The result in b belongs to a Gabor filter with medium kernel
size. As the size of the Gabor filter gets larger in c, it reveals larger text lines on the
page.
site. To reduce the effect of scale, mean and variance are not computed using
the same height and width as the site but by using a patch centered on the
site but with a size proportional to the local height of text components (which
comes from the height map) at that site.
Some global feature functions are used that do not depend on any observation.
These functions are noted below. In these function y c refers to the label
of the current site at the center and y t , y l and y tl refer to labels on the top,
left and top-left of the site, respectively. Labels may be 1 for text and 0 for
non-textual sites. Note that these functions are separate independent feature
functions that each takes its own weight while training. Thus, they cannot be
merged into a single function.
f = [y c = y l ]
f = [y c = y t ]
f = [y c = 0] × [y l = 0]
f = [y c = 0] × [y l = 1]
f = [y c = 1] × [y l = 0]
f = [y c = 1] × [y l = 1]
f = [y c = 0] × [y t = 0]
f = [y c = 0] × [y t = 1]
f = [y c = 1] × [y t = 0]
f = [y c = 1] × [y t = 1]
64