| 基于多特征组合的图像纹理分类 |
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| 引用本文： | 黄荣娟,姜佳欣,唐银凤,卢昕.基于多特征组合的图像纹理分类[J].计算机应用与软件,2011,28(8):12-16,46. |
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| 作者姓名： | 黄荣娟 姜佳欣 唐银凤 卢昕 |
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| 作者单位： | 1. 武汉大学信号处理实验室,武汉,湖北,430079
2. 武汉大学测控技术与仪器系,武汉,湖北,430079 |
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| 基金项目： | 国家自然科学基金(60872131) |
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| 摘 要： | 在对纹理图像进行特征提取的算法中,高斯马尔可夫随机场(GMRF)、局部二值模式(LBP)和灰度共生矩阵(GLCM)这三种算法应用的较为广泛.常见的图像纹理分类做法是取某一种特征提取算法得到各种纹理的特征空间,进而配合分类算法进行分类.然而,这种做法的不足之处在于未能充分利用各种特征之间的关联,且选取某一种特征提取算法建...
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| 关 键 词： | 纹理分类 高斯马尔可夫随机场 局部二值模式 灰度共生矩阵 特征组合 |
FEATURE COMBINATION BASED IMAGE TEXTURE CLASSIFICATION |
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| Huang Rongjuan,Jiang Jiaxin,Tang Yinfeng,Lu Xin.FEATURE COMBINATION BASED IMAGE TEXTURE CLASSIFICATION[J].Computer Applications and Software,2011,28(8):12-16,46. |
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| Authors: | Huang Rongjuan Jiang Jiaxin Tang Yinfeng Lu Xin |
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| Affiliation: | Huang Rongjuan1 Jiang Jiaxin1 Tang Yinfeng1 Lu Xin2 1(Department of Measuring and Control Technology and Instrumentations,Wuhan University,Wuhan 430079,Hubei,China) 2(Signal Processing and Modern Communication Lab,China) |
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| Abstract: | Among texture image feature extraction algorithms,Gaussian Markov Random Field(GMRF),Local Binary Patterns(LBP) and Gray Level Co-occurrence Matrix(GLCM) are the three comparatively widely used ones.The common image texture classification method is to choose one kind of feature extraction algorithm to obtain the feature space of various kinds of textures,then to cooperate with the classification algorithm for classification.However there are also weaknesses in the approach.On the one hand it doesn't fully u... |
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| Keywords: | Texture classification Gaussian Markov Random Field(GMRF) Local Binary Patterns(LBP) Gray Level Co-occurrence Matrix(GLCM) Feature combination |
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