[1]葛琦,邵文泽,李海波. 一种新的轮廓-局部区域分割模型及对偶算法[J].计算机技术与发展,2017,27(07):87-90.
　GE Qi,SHAO Wen-ze,LI Hai-bo. A New Contour-local-region Segmentation Model and Dual Algorithm[J].,2017,27(07):87-90.
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 一种新的轮廓-局部区域分割模型及对偶算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年07期
页码:
87-90
栏目:
智能、算法、系统工程
出版日期:
2017-07-10

文章信息/Info

Title:
 A New Contour-local-region Segmentation Model and Dual Algorithm
文章编号:
1673-629X（2017)07-0087-04
作者:
 葛琦; 邵文泽; 李海波
 南京邮电大学 通信与信息工程学院
Author(s):
 GE Qi; SHAO Wen-ze; LI Hai-bo
关键词:
 ; 轮廓-局部区域; 活动轮廓模型; 曲率拟合项; 对偶算法
Keywords:
 ; contour-local-region; active contour model ; curvature fitting term; dual algorithm
分类号:
TP391
文献标志码:
A
摘要:
 基于区域的变分活动轮廓模型能够较好地处理图像模糊边界并且不易受初始轮廓线和噪声的影响.然而,传统区域模型通常以粗划分区域内的图像信息作为活动轮廓曲线演化的驱动力,分割精度有限,并且容易受到图像灰度不均匀性的影响.为此,提出了一种新的轮廓-局部区域分割模型.新模型通过提取活动轮廓曲线邻域内的局部统计信息作为推动曲线演化的区域项,并引入曲率拟合项来捕捉目标的拐点和细长结构.针对模型求解中正则项的非可微性使计算效率较低并具有数值不稳定性的问题,通过引入辅助变量将原最优化问题转化为若干个低复杂度子问题进行求解,提出了一种快速对偶算法.医学核磁共振图像分割实验表明,所提出的模型和算法的准确性和运行效率均有明显的提高.
Abstract:
 The variational region-based models often have the better performance for the images with weak object boundaries and are less sensitive to the initial contours and noise.However,in traditional region-based models,because their guidance force for contour evolution is only based on the extracted image information of rough partitioned region,they are limited in accuracy of segmentation and also often easily sensitive to the non-homogeneity of the image.A new Contour-Local-Region (CLR) segmentation model has been proposed in which the local statistic information in the neighborhood of the curve has been explored as the region term to drive the curve evolution,and a curvature fitting term has been applied to capture the inflexion,acute structure of the object.To overcome the un-stability and the non-differentiability of the numerical solution of regularization term,the original minimizing problem is transformed into several sub-problems with low computational complexity by introducing auxiliary variables,and then a fast dual algorithm has been proposed.Experimental results on medical Magnetic Resonance (MR) image demonstrate precision and efficiency of the proposed model.

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更新日期/Last Update: 2017-08-22