Distance regularization energy terms in level set image segment model: A survey
文献类型：期刊论文
| 作者 | Zou, Le1,4,5; Weise, Thomas2; Huan, Qian-Jing3; Wu, Zhi-Ze2; Song, Liang-Tu1,5 ; Wang, Xiao-Feng4
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| 刊名 | NEUROCOMPUTING
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| 出版日期 | 2022-06-28 |
| 卷号 | 491 |
| 关键词 | Image segmentation Level set Double well potential function Distance regularization energy term Diffusion rate |
| ISSN号 | 0925-2312 |
| DOI | 10.1016/j.neucom.2021.09.080 |
| 通讯作者 | Wang, Xiao-Feng(xfwang@hfuu.edu.cn) |
| 英文摘要 | The level set is a classical image segmentation model. In order to achieve its stable evolution, the level set function should be a signed distance function (SDF). However, due to the common appearance of irregularities, it must periodically be initialized in order to remain a SDF near the zero level set. Distance regularization terms have been used to maintain the stable evolution of the level set function. We provide a survey of the various distance regularization potential functions. Firstly, we summarize many kinds of distance regularization potential functions studied in the literature. We then divide them into five classes according to the type of potential function. Secondly, we analyze the properties of every class of potential functions and their diffusion rate functions. Finally, to demonstrate the effectiveness of the distance regularization potential functions, we apply them with a region based level set energy functional for image segmentation. Experimental analyses are conducted to compare the segmentation performance of various distance regularization potential functions when combined with the classical Chan Vese model. (c) 2022 Elsevier B.V. All rights reserved. |
| WOS关键词 | ACTIVE CONTOUR MODEL ; FUZZY C-MEANS ; PROBABILISTIC NEURAL-NETWORKS ; FINDING ARBITRARY ROOTS ; SCALABLE FITTING ENERGY ; INTENSITY INHOMOGENEITY ; RE-INITIALIZATION ; DRIVEN ; POLYNOMIALS ; ALGORITHM |
| 资助项目 | National Natural Science Foundation of China[61672204] ; National Natural Science Foundation of China[61673359] ; National Natural Science Foundation of China[61806068] ; Anhui Provincial Natural Science Foundation[1908085MF184] ; Anhui Provincial Natural Science Foundation[1908085QF285] ; Key Research Plan of Anhui Province[202104d07020006] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000806853000004 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Anhui Provincial Natural Science Foundation ; Key Research Plan of Anhui Province |
| 源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/131259]  |
| 专题 | 中国科学院合肥物质科学研究院 |
| 通讯作者 | Wang, Xiao-Feng |
| 作者单位 | 1.Univ Sci & Technol China, Hefei 230026, Anhui, Peoples R China 2.Hefei Univ, Sch Artificial Intelligence & Big Data, Inst Appl Optimizat, Hefei 230601, Anhui, Peoples R China 3.Hefei Univ, Coll Bioengn Food & Environm Sci, Hefei 230601, Anhui, Peoples R China 4.Hefei Univ, Sch Artificial Intelligence & Big Data, Anhui Prov Engn Lab Big Data Technol Applicat Urb, Hefei 230601, Anhui, Peoples R China 5.Chinese Acad Sci, Hefei Inst Phys Sci, POB 1130, Hefei 230031, Anhui, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zou, Le,Weise, Thomas,Huan, Qian-Jing,et al. Distance regularization energy terms in level set image segment model: A survey[J]. NEUROCOMPUTING,2022,491. |
| APA | Zou, Le,Weise, Thomas,Huan, Qian-Jing,Wu, Zhi-Ze,Song, Liang-Tu,&Wang, Xiao-Feng.(2022).Distance regularization energy terms in level set image segment model: A survey.NEUROCOMPUTING,491. |
| MLA | Zou, Le,et al."Distance regularization energy terms in level set image segment model: A survey".NEUROCOMPUTING 491(2022). |
入库方式： OAI收割
来源：合肥物质科学研究院
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