| 基于支持向量机和灰度共生矩阵的纹理图像分割方法 |
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| 引用本文： | 陈英,杨丰玉,符祥. 基于支持向量机和灰度共生矩阵的纹理图像分割方法[J]. 传感器与微系统, 2012, 31(9): 60-63 |
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| 作者姓名： | 陈英 杨丰玉 符祥 |
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| 作者单位： | 1. 南昌航空大学软件学院,江西南昌330063;吉林大学计算机科学与技术学院,吉林长春130012
2. 南昌航空大学软件学院,江西南昌,330063 |
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| 基金项目： | 航空科学基金资助项目(2010ZC56006);江西省教育厅科技计划资助项目(GJJ10189) |
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| 摘 要： | 图像分割是计算机视觉领域的研究热点。灰度共生矩阵是图像灰度的二阶统计度量,反映了纹理图像灰度在方向、局部邻域和变化幅度的综合信息,以能量、对比度、熵、差方差和差熵作为纹理图像的特征,利用支持向量机(SVM)对这些特征进行训练和分类,以达到纹理图像分割的目的。详细说明了纹理图像的分割过程,同时分析了不同参数情况下对分割精度的影响。针对Brodatz纹理库的实验结果表明:该方法具有较好的分割效果。
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| 关 键 词： | 支持向量机 灰度共生矩阵 纹理特征提取 图像分割 |
Method of texture image segmentation based on SVM and gray level co-occurrence matrix |
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| CHEN Ying , YANG Feng-yu , FU Xiang. Method of texture image segmentation based on SVM and gray level co-occurrence matrix[J]. Transducer and Microsystem Technology, 2012, 31(9): 60-63 |
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| Authors: | CHEN Ying YANG Feng-yu FU Xiang |
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| Affiliation: | 1(1.School of Software,Nanchang Hangkong University,Nanchang 330063,China; 2.School of Computer Science and Technology,Jilin University,Changchun 130012,China) |
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| Abstract: | Image segmentation is a hotspot in the field of computer vision.Gray level co-occurrence matrix is a second-order statistical measure of image grayscale which reflects the comprehensive information of image grayscale in the direction,local neighborhood and magnitude of changes,support vector machine(SVM) is used in training and classification of these features,which are energy,contrast,entropy,different variance and different entropy stand for textural image,to achieve the purpose of texture image segmentation.The process of texture image segmentation is explained,and the effect of different parameters on the segmentation precision is analyzed.The experimental results of Brodatz texture library show that this method has better segmentation effect. |
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| Keywords: | support vector machine(SVM) gray level co-occurrence matrix textural feature extraction image segmentation |
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