Fast image segmentation based on multilevel banded closed-form method

被引:6
作者
Han, Shoudong [2 ]
Tao, Wenbing [1 ]
Wu, Xianglin [2 ]
Tai, Xue-cheng [3 ]
Wang, Tianjiang [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Inst Syst Engn, Wuhan 430074, Peoples R China
[3] Nanyang Technol Univ, Div Math Sci, Sch Math & Phys Sci, Singapore 637616, Singapore
基金
中国国家自然科学基金;
关键词
Graph Cuts; Closed-form; Multi-seeds; Interactive image segmentation; GRAPH CUTS;
D O I
10.1016/j.patrec.2009.10.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:216 / 225
页数:10
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