A Graph Multi-separator Problem for Image Segmentation
Jannik Irmai Shengxian Zhao Jannik Presberger Bjoern Andres
We propose a novel abstraction of the image segmentation task in the form of
a combinatorial optimization problem that we call the multi-separator problem.
Feasible solutions indicate for every pixel whether it belongs to a segment or
a segment separator, and indicate for pairs of pixels whether or not the pixels
belong to the same segment. This is in contrast to the closely related lifted
multicut problem where every pixel is associated to a segment and no pixel
explicitly represents a separating structure. While the multi-separator problem
is NP-hard, we identify two special cases for which it can be solved
efficiently. Moreover, we define two local search algorithms for the general
case and demonstrate their effectiveness in segmenting simulated volume images
of foam cells and filaments.