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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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图像的纹理分析，共生矩阵等-Image texture analysis, such as co-occurrence matrix
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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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灰度共生矩阵和灰度梯度共生矩阵纹理提取，能够计算纹理的多个测度-Gray Level Co-occurrence matrix and gray-gradient co-occurrence matrix texture extraction
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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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用于纹理特征的提取：采用灰度共生矩阵的方法求取纹理特征-used in the texture vales exacting:by using gray-level co-occurrence matrix to exact the texture values.
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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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matlab最全纹理特征代码，灰度共生矩阵软件自带，就不传了。里面有tamura六个参数，灰度梯度共生矩阵的纹理特征，还有熵。-matlab the best texture feature code, the GLCM software comes not passed. Tamura six parameters, the shades of gray co-occurrence matrix texture features, as well as entropy.
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适用于二维图像的共度共生矩阵纹理特征提取,尤其是在医学处理方向-Co-occurrence Matrix
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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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A statistical method of examining texture that considers the spatial relationship of
pixels is the gray-level co-occurrence matrix (GLCM), also known as the gray-level
spatial dependence matrix. The GLCM functions characterize the texture of an ima
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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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