A Novel Graph Cut Algorithm for Weak Boundary Object Segmentation

Image segmentation plays an important role in high-level visual recognition tasks. In recent years, the combinatorial graph cut algorithm has been successfully applied to image segmentation because it offers numerically robust global minimum. For low-level image segmentation, intensity is a widely used regional cue. However, when comes to weak boundary, it is often not enough to discriminate the object of interest. In this paper, we extend the standard graph cut algorithm by taking into account the gradient direction of neighboring pixels as an additional cue. A new energy function is proposed to fuse the intensity and gradient cues. Experimental results show that our method is more robust and helpful to detect the low-contrast boundaries.

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