Fast image segmentation based on multilevel banded closed-form method

Authors:
Shoudong Han;Wenbing Tao;Xianglin Wu;Xue-cheng Tai;Tianjiang Wang
Affiliations:
Institute of Systems Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;Institute of Systems Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637616, Singapore;School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
Venue:
Pattern Recognition Letters
Year:
2010

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Abstract

In this paper, a fast interactive image segmentation method is developed. The method combines the GrabCut algorithm with the multilevel banded closed-form (MLBCF) technique to achieve the acceleration. The GrabCut method is first applied on a low-resolution image to obtain the segmentation. The coarse labeling is then propagated to the higher-resolution level by using the banded closed-form method with the locally linear assumption. Some post-processing, such as alpha thresholding, probability classification and multi-seeds banded Graph Cuts, is applied to assign the final labeling. For experimental comparison, we also implement the multilevel banded Graph Cuts (MLBGC) method based on GrabCut algorithm. Experiments using synthesized noisy images and real natural scene images demonstrate the superior performance of the proposed method in terms of segmentation accuracy, computation efficiency and memory usage.