.
6
.
Flexible shape extraction
(snakes and other
techniques)
6.1 Overview
The previous chapter covered finding shapes by matching. This implies knowledge of a model
(mathematical or template) of the target shape (feature). The shape is fixed in that it is flexible
only in terms of the parameters that define the shape, or the parameters that define a template’s
appearance. Sometimes, however, it is not possible to model a shape with sufficient accuracy,
or to provide a template of the target as needed for the generalized Hough transform (GHT). It
might be that the exact shape is unknown or that the perturbation of that shape is impossible to
parameterize. In this case, we seek techniques that can evolve to the target solution, or adapt
their result to the data. This implies the use of flexible shape formulations. This chapter presents
four techniques that can be used to find flexible shapes in images. These are summarized in
Table 6.1 and can be distinguished by the matching functional used