Features for Active Contour and Surface Segmentation: A Review

Abstract

Active contour and active surface models are image segmentation methods which offer a solid mathematical background, reduced computational time, smooth boundaries and, in many cases, also robustness in presence of noise. In other cases, due to the complexity of the images, active contour-surface models do not provide good results. However, their performance can be improved by taking into account more strategic image features that affect the evolution of the active contours-surfaces. This review seeks to explore the features used in literature for this goal, the related topic of feature reduction/selection, and the type of images involved. Considerations about limitations and possible future extensions are also presented.