Curve Propagation, Level Set Methods and Grouping

Image segmentation and object extraction are among the most well addressed topics in computational vision. In this chapter we present a comprehensive tutorial of level sets towards a flexible frame partition paradigm that could integrate edge-drive, regional-based and prior knowledge to object extraction. The central idea behind such an approach is to perform image partition through the propagation planar curves/surfaces. To this end, an objective function that aims to account for the expected visual properties of the object, impose certain smoothness constraints and encode prior knowledge on the geometric form of the object to be recovered is presented. Promising experimental results demonstrate the potential of such a method.