Editing Image segmentation (section)

== Model-based segmentation ==

The central assumption of model-based approaches is that the structures of interest have a tendency towards a particular shape. Therefore, one can seek a probabilistic model that characterizes the shape and its variation. When segmenting an image, constraints can be imposed using this model as a prior.<ref name="StaibDuncan1992">{{cite journal|last1=Staib|first1=L.H.|last2=Duncan|first2=J.S.|title=Boundary finding with parametrically deformable models|journal=IEEE Transactions on Pattern Analysis and Machine Intelligence|volume=14|issue=11|year=1992|pages=1061–1075|issn=0162-8828|doi=10.1109/34.166621}}</ref> Such a task may involve (i) registration of the training examples to a common pose, (ii) probabilistic representation of the variation of the registered samples, and (iii) statistical inference between the model and the image. Other important methods in the literature for model-based segmentation include [[active shape model]]s and [[active appearance model]]s.