结合半局部信息与结构张量的无监督纹理图像分割

赵在新; 成礼智

doi:10.11834/jig.20110411

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专辑

结合半局部信息与结构张量的无监督纹理图像分割
Unsupervised texture segmentation combined semi-local image information and structure tensor
2011年16卷第4期页码：559-565
网络出版：2011-04-26，

纸质出版：2011
DOI： 10.11834/jig.20110411
稿件说明：

移动端阅览

赵在新, 成礼智. 结合半局部信息与结构张量的无监督纹理图像分割[J]. 中国图象图形学报, 2011,16(4):559-565. DOI： 10.11834/jig.20110411.

Zhao Zaixin, Cheng Lizhi. Unsupervised texture segmentation combined semi-local image information and structure tensor[J]. Journal of Image and Graphics, 2011, 16(4): 559-565. DOI： 10.11834/jig.20110411.

摘要

针对纹理的半局部性质与方向性，提出一种基于活动轮廓的无监督双纹理图像分割方法。首先分析基于半局部信息的纹理特征表示方法，指出其不能有效区分纹理的方向特征。然后利用半局部信息结合非线性结构张量构造4通道纹理特征，采用混合高斯模型作为纹理特征的概率密度函数，模型的数值求解采用分裂Bregman方法。新方法充分考虑纹理结构的周期性与方向特性，实验结果表明，其能够处理复杂的双纹理图像分割任务，同时具有高效与无监督特性。

Abstract

An unsupervised two-phase texture segmentation method based on active contour was proposed. First

the texture feature extraction approach based on semi-local image information was analyzed

which revealed that it could not represent texture’s orientation information. In order to segment texture images containing periodic and orientational character

a four-channel texture feature was achieved combing semi-local image information with nonlinear structure tensor. Then Gaussian mixture model was adopted to describe the probability density function of the features. Numerical algorithms were based on split Bregman method. Experimental results for both nature and synthetic texture images show that our method could cope with complex segmentation tasks. Meanwhile it is effective and unsupervised.