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提取图像的GLCM矩阵，并计算出Haralick建议的14个特征值-Extract images GLCM matrix, and calculate the 14 Haralick features of the proposed values
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图像纹理特征描述了在图像中反复出现的局部模式和它们的排列规则，反应宏观意义上灰度变化的一些规律，编程实现基于灰度共生矩阵的图像纹理特征提取-Image texture features described in the repeated images of local models and their regular arrangement, the reaction intensity changes in the macro sense, some laws, programming, GL
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支持向量机(svM)是一种新的机器学习技术。本文采用一对一方法构建多分类SVM
分类器。利用常用的灰度共生矩阵方法提取图像纹理特征，组成特征向量，输入构建好的SVM
多分类器中进行分类。对从Brodatz纹理库中选取的4张纹理图像进行了分类实验，取得较好的
分类结果-Support vector machine (svM) is a new machine learning techniques. In this paper, one way to build a multi-cla
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灰度共生矩阵提取图像纹理特征，可输入rgb图像，出来的结果较为清晰。带文字说明-GLCM texture features extracted images translate
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glcm mean in matlab by armin moghimi devloped GLCM_Features1 helps to calculate the features from the different GLCMs
that are input to the function. The GLCMs are stored in a i x j x n
matrix, where n is the number of GLCMs calculated usually
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This project is extracting GLCM features and do the images
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将图像进行三层离散小波变换得到三幅高频图像，再利用function可利用灰度共生矩阵得到三幅高频图像的纹理特征-The image is three discrete wavelet transform three high-frequency images, re-use function can be used to obtain GLCM texture features three high-frequency image
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首先使用灰度共生矩阵提取图像纹理特征，之后使用灰度共生矩阵的熵值与相关性系数作为纹理参数，用k-means聚类算法实现遥感图像的云检测-First of all, the gray co-occurrence matrix is used to extract the image texture features, then the entropy and correlation coefficients of the GLCM are used as texture parameters, a
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灰度共生矩阵用于提取图像的特征，用于图像识别和分类(Gray level co-occurrence matrix is used to extract the features of images, and is used for image recognition and classification)
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