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| 基于GLCM和EM算法的纹理图像分割 | |
| 引用本文： | 黄宁宁,贾振红,杨杰,庞韶宁.基于GLCM和EM算法的纹理图像分割[J].通信技术,2011,44(1):48-49,52. |
| 作者姓名： | 黄宁宁 贾振红 杨杰 庞韶宁 |
| 作者单位： | 1. 新疆大学,信息科学与工程学院,新疆,乌鲁木齐,830046 2. 上海交通大学,图像处理与模式识别研究所,上海,200240 3. 新西兰奥克兰理工大学,知识工程与开发研究所,新西兰,奥克兰,1020 |
| 摘 要： | 基于纹理图像的特征,提出了基于灰度共生矩阵（GLCM）和快速极大似然估计（EM）算法相结合的纹理图像分割新算法,为了获得较好的纹理图像分割结果该算法采用灰度共生矩阵的三个常用特征并在四个方向上求平均,从而克服了方向的影响。采用欧式距离度量函数求得两特征向量的距离。通过用改进EM算法对距离矩阵进行聚类,得到纹理图像的初始分割结果,最后用形态学的方法实现对纹理图像边界的精确定位。 |
| 关 键 词： | 灰度共生矩阵 EM算法 纹理分割 距离函数 |
Texture Segmentation based on Gray-Level Co-occurrence Matrix Features and EM Algorithm |
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| HUANG Ning-ning,JIA Zhen-hong,YANG Jie,PANG Shao-ning.Texture Segmentation based on Gray-Level Co-occurrence Matrix Features and EM Algorithm[J].Communications Technology,2011,44(1):48-49,52. | |
| Authors: | HUANG Ning-ning JIA Zhen-hong YANG Jie PANG Shao-ning |
| Affiliation: | ③(①College of Information Science and Engineering,Xinjiang University,Urumuqi Xinjiang 830046,China; ②Institute of Image Processing and Pattern Recognition,Shanghai Jiaotong University,Shanghai 200240,China; ③Knowledge Engineering and Discovery Research Institute,Auckland University of Technology,Auckland 1020,New Zealand) |
| Abstract: | This paper proposes a textures segmentation algorithm based on gray-Level co-occurrence matrix features and EM.Three texture features is computed,thus to gain better result.The average measurements of all four angles are usually used in calculating GLCM for reducing the influence of angle.The distance between two texture feature vectors are measure.To derive the initial segmentation result,distance matrix is used as the feature vector and the improved expectation maximization image segmentation is applied to achieving effective segmentation.Finally,by using the method of morphology,the accurate localization of region boundaries is realized. |
| Keywords: | gray-Level co-occurrence matrix(GLCM) EM algorithm texture segmentation distance function |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
