文件名称:Analysisoftexturefeatureextractedbygraylevelco2occ
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为使灰度共生矩阵(GLCM)提取的特征值较好地表达纹理信息,对Brodatz纹理库图片进行了大量实验。
首先测试了各构造参数对关键特征统计量的影响,给出了特征值随参数变化的规律,确立了构造参数的合理取值 然
后测试了图像旋转和大小变化对所提取特征值的影响-In order to grayscale co-occurrence matrix (GLCM) features extracted texture to express the value of good information and pictures on the Brodatz texture library has a large number of experiments. First, test the key features of various structural parameters on the impact of statistics given parameters of the feature value with changes in the law establishing the reasonable value of structural parameters and then test the changes in image rotation and size of the extracted characteristic values of
首先测试了各构造参数对关键特征统计量的影响,给出了特征值随参数变化的规律,确立了构造参数的合理取值 然
后测试了图像旋转和大小变化对所提取特征值的影响-In order to grayscale co-occurrence matrix (GLCM) features extracted texture to express the value of good information and pictures on the Brodatz texture library has a large number of experiments. First, test the key features of various structural parameters on the impact of statistics given parameters of the feature value with changes in the law establishing the reasonable value of structural parameters and then test the changes in image rotation and size of the extracted characteristic values of
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Analysisoftexturefeatureextractedbygraylevelco2occurrencematrix\灰度共生矩阵提取纹理特征的实验结果分析.pdf
Analysisoftexturefeatureextractedbygraylevelco2occurrencematrix
Analysisoftexturefeatureextractedbygraylevelco2occurrencematrix