| A Unified Tensor Level Set for Image Segmentation | |
| Wang, Bin1; Gao, Xinbo1; Tao, Dacheng2; Li, Xuelong3; B. Wang | |
| 2010-06-01 | |
| 发表期刊 | IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
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| ISSN | 1083–4419 |
| 卷号 | 40期号:3页码:857-867 |
| 摘要 | This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt-and pepper-type noise. Second, considering the local geometrical features, e. g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method. |
| 文章类型 | Article |
| 关键词 | Gabor Filter Bank Geometric Active Contour Image Segmentation Level Set Method Partial Differential Equation (Pde) And Tensor Field |
| 学科领域 | 信号与模式识别 |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1109/TSMCB.2009.2031090 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | DISCRIMINANT-ANALYSIS ; MODELS ; FLOW ; RECOGNITION ; CURVATURE |
| 语种 | 英语 |
| WOS研究方向 | Automation & Control Systems ; Computer Science |
| WOS类目 | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
| WOS记录号 | WOS:000277774700027 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/8558 |
| 专题 | 光谱成像技术研究室 |
| 通讯作者 | B. Wang |
| 作者单位 | 1.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 2.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore 3.Chinese Acad Sci, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Bin,Gao, Xinbo,Tao, Dacheng,et al. A Unified Tensor Level Set for Image Segmentation[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,2010,40(3):857-867. |
| APA | Wang, Bin,Gao, Xinbo,Tao, Dacheng,Li, Xuelong,&B. Wang.(2010).A Unified Tensor Level Set for Image Segmentation.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,40(3),857-867. |
| MLA | Wang, Bin,et al."A Unified Tensor Level Set for Image Segmentation".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 40.3(2010):857-867. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| A Unified Tensor Lev（2230KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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