Biomedical Engineering Reference
In-Depth Information
images where there are weak edges or noisy regions preventing the aforemen-
tioned snakes to perform at their best. Although GGVFs have been reported only
using gray level image gradients, we can also apply them to “color” gradients
(obtained as described in Section 10.6), which allows direct comparison with
the color RAGS. It must also be noted that the GGVF can sometimes perform
better than we have shown in some of the following examples as long as it is
initialized differently, i.e. much closer to the desired boundary. In all the exper-
iments, we have initiated the geometric, GGVF, and RAGS snakes at the same
starting position, unless specifically stated.
10.9.1 Preventing Weak-Edge Leakage
We first illustrate the way weak-edge leakage is handled on a synthetic image.
The test object is a circular shape with a small blurred area on the upper right
boundary as shown in Fig. 10.15.
The standard geometric snake steps through the weak edge because the in-
tensity changes so gradually that there is no clear boundary indication in the
edge map. The RAGS snake converges to the correct boundary since the ex-
tra diffused region force delivers useful global information about the object
boundary and helps prevent the snake from stepping through. Figure 10.16
shows, for the test object in Fig. 10.15, the edge map, the stopping function
g
(
·
), its gradient magnitude
|∇
g
(
·
)
|
, the region segmentation map
S
, and the
vector map of the diffused region force
R
.
Figure 10.15: Weak-edge leakage testing on a synthetic image. Top row:
geodesic snake steps through. Bottom row: RAGS snake converges properly
using its extra region force.
