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论文:2014,Vol:32,Issue(3):434-439 |
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引用本文： |
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周三平, 滕炯华, 黄保山, 徐婧林. 基于边缘信息与偏移场矫正的多相Chan-Vese图像分割模型[J]. 西北工业大学 |
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Zhou Sanping, Teng Jionghua, Huang Baoshan, Xu Jinglin. A Multiphase Chan-Vese Model Using Edge Information and Bias Field Correction for Image Segmentation[J]. Northwestern polytechnical university |
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| 基于边缘信息与偏移场矫正的多相Chan-Vese图像分割模型 |
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| 周三平, 滕炯华, 黄保山, 徐婧林 |
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| 西北工业大学 自动化学院, 陕西 西安 710172 |
| 摘要: |
| 图像中存在的灰度不均匀现象与演化曲线被错误的目标边缘引导给图像的多相分割带来了很大困难。针对这一问题,利用对数变换将乘性偏移场转化成线性偏移场,通过核函数引入局部灰度信息建立了偏移场矫正模型。此外,运用水平集函数与图像梯度的方向信息重建了边缘指示函数,增强了演化曲线对正确目标边缘的识别能力。人工合成图像和自然图像的分割实验结果表明文中提出的模型能够取得令人满意的分割结果。 |
| 关键词:
图像分割
多相水平集
偏移场矫正
边缘指示函数
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| A Multiphase Chan-Vese Model Using Edge Information and Bias Field Correction for Image Segmentation |
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| Zhou Sanping, Teng Jionghua, Huang Baoshan, Xu Jinglin |
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| Department of Automatic Control, Northwestern Polytechnical University, Xi'an 710072, China |
| Abstract: |
| Intensity inhomogeneity and the curve of level set evolution misguiding the edge of target cause consider-able difficulty in image segmentation. This paper proposes a new method in which a multiplicative bias field function is converted into its linear form with logarithmic transformation;the intensity information in local region is extracted to the bias field function by using kernel function; a new bias field correction model is built based on variational method. In addition, the edge indicator function is rebuilt by comprehensive utilization of the direction information of the level set function and image; this improves the ability of the evolving curve to recognize target boundaries. Experimenntal results for synthetic and real images and their analysis show preliminarily that the performances of our method are desirable. |
| Key words:
eigenvalues and eigenfunctions
experiments
functions
Gaussian noise (electronic)
image segmentation
mathematical models
MATLAB
topology
variational techniques
bias field correction
edge indicator function
multiphase level set
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| 收稿日期: 2013-10-24
修回日期:
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| DOI: |
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| 作者简介: 周三平(1988-),西北工业大学硕士研究生,主要从事图像处理及模式识别的研究。
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参考文献: |
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[1] Chan T F, Vese L. Active Contours without Edge[J]. IEEE Trans on Image Processing, 2001, 10(2): 266-277
[2] Vese L, Chan T F. A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model[J]. International Journal of Computer Vision, 2002, 50(3): 271-293
[3] 黄保山, 滕炯华. 基于偏移场修正的 C-V 模型水平集图像分割算法[J]. 西北工业大学学报. 2013, 31 (2): 218-222 Huang Baoshan, Teng Jionghua. A Novel Algorithm of Level Set Image Segmentation Based on Bias Field Correction C-V Model [J]. Journal of Northwestern Polytechnical University, 2013, 31 (2): 218-222 (in Chinese)
[4] Li Chunming, Xu Chengyang. Distance Regularized Level Set Evolution and Its Application to Image Segmentation[J]. IEEE Trans on Image Process 2010, 12(12): 3243-3254
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[6] Wang Li, Li Chunming. Active Contours Driven by Local and Global Intensity Fitting Energy with Application to Brain MR Image Segmentation[J]. Computerized Medical Imaging and Graphics, 2009, 33(7): 520-531
[7] Li C, Xu C, Gui C, et al. Level Set Evolution without Re-Initialization: A New Variational Formulation [C]//IEEE International Conference on Computer Vision and Patttern Recognition (CVPR), 2005, 1: 430-436 |
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