Biomedical Engineering Reference
In-Depth Information
Figure 10.6: Example of a color image. (Left) original image with initial snake
and (right) converged geometric snake (with a minor convergence problem in
the top right corner of the snake)—from [6] (color slide).
10.2.2 Shortcomings of the Geometric Snake
Geometric active contour models have the significant advantage over classical
snakes that changes in topology due to the splitting and merging of multiple
contours are handled in a natural way. However, they suffer in two specific
ways:
1. They use only local information and hence are sensitive to local minima.
This means they are attracted to noisy pixels and can fail to converge
on the desired object when they rest at such strong “features.” They fail
to recognize, possibly weaker but true features further away in the im-
age landscape, for lack of a better global understanding of the image. An
example is shown in Fig. 10.7 (left).
Figure 10.7: Noise sensitivity and weak-edge leakage problems. In each case
the evolving snake is shown in a light color and the final snake in a dark one.
