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（图像处理）用统计法求出共生矩阵 并给出纹理信息-(image processing) is calculated by using statistical co-occurrence matrix and gives texture
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灰度共生矩阵和灰度梯度共生矩阵的提取方式，是比较重要的纹理特征提取方法，用matlab实现的-co-occurrence matrix and GGCM extraction, is the more important Texture feature extraction methods, achieved using Matlab
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结合特征参数间相关性矩阵与木材纹理自身的特征, 从灰度共生矩阵的11 个特征参数中提取5 个较
独立的特征参数。利用可分性判据确定适于描述木材纹理的灰度共生矩阵构造因子取值( d=2, g=16) 。,Combination of characteristic parameters of inter-correlation matrix with the wood texture of its own features, from the gray level co-occurrence ma
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对图像的纹理特征进行提取，主要基于灰度共生矩阵，然后计算二次统计量（即特征）-Texture features for image extraction, mainly based on gray level co-occurrence matrix, and then calculate the amount of secondary statistics (ie features)
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由灰度共现矩阵提取纹理特征：能量，惯性矩，相关性，熵，有完整的交互界面,By the gray co-occurrence matrix texture features extraction: energy, moment of inertia, relevance, entropy, there is a complete interface
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matlab编写的用于实现灰度共生矩阵，灰度-梯度共生矩阵，灰度直方图，协方差系数，LOG滤波器的源代码了。全部经过测试，可以直接使用。对于做纹理分析很有帮助。一共有五个代码-matlab prepared for the realization of Gray Level Co-occurrence matrix, gray- gradient co-occurrence matrix, gray histogram, covariance coefficients, LOG source c
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这是基于灰度共生矩阵提取纹理特征重要参数的代码-This is based on gray level co-occurrence matrix texture features extracted the important parameters of the code
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基于共生矩阵纹理特征提取，d=1,θ=0°,45°,90°,135°共四个矩阵,所用图像灰度级均为256-Co-occurrence matrix based texture feature extraction, d = 1, θ = 0 °, 45 °, 90 °, 135 ° total of four matrices, the use of gray-scale images are 256
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纹理分析－灰度共现矩阵算法实现，通常将图像划分成若干个纹理块计算。-Texture Analysis- gray co-occurrence matrix algorithm implementation, usually the image is divided into a number of texture calculation block.
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频率域熵图，两个窗口，熵的径向和角向分布，便于分析纹理，还有一个自己写的gabor变换，请参考。-Frequency domain entropy map, two windows, the entropy of the radial and angular distribution, to facilitate analysis of texture, there is a transform gabor wrote it myself, please refer to.
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基于灰度共生矩阵的纹理特征提取方法实现目标的识别-Gray-level co-occurrence matrix based texture feature extraction methods to achieve the target identification
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提取纹理特征参数,主要是灰度共生矩阵源代码，用于图像处理-gray level co-matrix source code,used for the image processing, to get the texture features
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基于图像纹理的特征提取，使用灰度共生矩阵方法。-Texture feature extraction based on the use of gray level co-occurrence matrix method.
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通过使用灰度共现矩阵的方法，装载BMP图像，并实现对人脸图像获得纹理特征计算-By using the gray level co-occurrence matrix method, loading BMP images, and to achieve the face image texture features were calculated
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求图像的灰度共生矩阵，并求其主要的特征参数-Gray Level Co-occurrence Matrix
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基于纹理特征提取灰度共生矩阵用于纹理判断-Extract gray level co-occurrence matrix based texture features for texture judgment
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图像纹理特征提取，包括分形维数，灰度游程长度，灰度共生矩阵等五种图像纹理特征。-To extract image texture features, including fractal dimension, length of gray-level run-length, gray level co-occurrence matrix and other five kinds of image texture features。
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基于灰度共生矩阵的纹理图像分类研究相关论文-Research on texture image classification based on gray level co-occurrence matrix
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利用灰度图 建共生矩阵 利用特征值 对纹理图像分割-The use of grayscale co-occurrence matrix to build the use of characteristic values of the texture map would like to partition
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灰度共生矩 阵即为灰度级的空间相关矩阵，以其为基础的统计方法通过对矩阵统计量的求取较好地提取到了纹理特征，通过选取关键参数编程并进行仿真实现，分别求取了四个方向的灰度共生矩阵及其特征量来分析图像 的纹理特征。(The gray level co-occurrence matrix is the gray level spatial correlation matrix. Based on the gray level co-occurrence matrix, the texture featu
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