基于LBP纹理特征的随机游走图像分割
Image segmentation with random walker based on LBP texture features
郭艳蓉 1蒋建国 2郝世杰 1詹曙 1李鸿3
作者信息
- 1. 合肥工业大学计算机与信息学院,安徽合肥230009
- 2. 合肥工业大学计算机与信息学院,安徽合肥230009;安全关键工业测控技术教育部工程研究中心,安徽合肥230009
- 3. 安徽医科大学第一附属医院骨科,安徽合肥230022
- 折叠
摘要
本文通过求解融入纹理特征信息的对称、半正定线性方程组,提出一种新的基于随机游走(Random Walker)的纹理图像分割算法.为了构造该方程组,首先通过局部二元模式(Local binary pattern,简称LBP)算子来描述纹理,将图像映射至不同纹理之间有显著区别的LBP图(LBP map)上,进而将其与梯度和几何信息结合并构造倒数型像素相似度,形成方程所需的权值矩阵,在随机游走模型下使已标号区域向未知区域传递,从而实现纹理图像分割.最后以纹理图像、噪声合成图像、MRI、CT图像为实验对象来验证算法的有效性.定性及定量实验结果表明,在多目标分割任务下,本方法有更好的有效性和精确性.
Abstract
In this paper,we propose a new random walker model for texture image segmentation through solving a symmetric,semi-positive-definite system of linear equations equipped with the texture information.In the construction of the equations,we perform the feature extraction based on Local Binary Pattern (LBP) and map the original image into the space where textures are distinguished from each other (called as LBP map).The similarity between the pixels is then constructed by combining the LBP,gradient and geometric feature in a reciprocal fashion.These similarities are formed as the edge weights of the graph,which helps the labels of the seeds propagate into the unlabeled regions during the random walker process.Experiments on the texture images,synthetic noise images and medical images shows that the proposed segmentation method extends the state-of-art random walker segmentation to texture images successfully and outperforms some other texture segmentation algorithms particularly on multi-label problem based on the qualitative and quantitative results.
关键词
纹理图像分割/随机游走/局部二元模式Key words
texture image segmentation/random walker/local binary pattern引用本文复制引用
出版年
2013
NETL
NSTL
维普
万方数据