Paper Title
Comparative Study On Graph Cuts For Image Segmentation

Abstract
Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in computer vision and graphics. In this paper we have analyzed mainly four techniques Graph cuts (GC), Iterative Graph Cuts (IGC), Multi-label Random walker (RW) and Lazy Snapping (LS). Graph Cut techniques are used for completely automatic high-level grouping of image pixels. Iterative Graph Cut technique allows some sort of user interaction for extracting objects from a complex background. Random Walker algorithm requires user specific labels and produce a segmentation where each segment is connected to a labeled pixel. Lazy Snapping provides instant visual feedback, snapping the cutout contour to the true object boundary efficiently despite the presence of ambiguous or low contrast edges. Keywords- Graph Cut, Iterated Graph cut, Lazy Snapping, Markovian Random Field