Alpha cut for interactive image segmentation of thin and elongated objects

摘要

Shrinking bias problem is a practical limitation of graph-cut-based methods for binary image segmentation. The detail parts with thin elongated object are not well preserved in graph cut minimisation as a result. The authors propose to use structure transferring to overcome the problem with an expanded L2 norm of colour difference. They also show that the structure-transferring output can be integrated into graph cuts as a counter-balance to shrinking problem. Experimental results show that the proposed alpha-cutting technique is effective and efficient in improving segmentation of thin elongated objects.