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1)  statistical and co-occurrence matrix
统计-共生矩阵
2)  co-occurrence matrix
共生矩阵
1.
The Gray Level of Image Co-occurrence Matrix
图像检索中灰度共生矩阵的构造与实现
2.
Image retrieval based on blocked histograms and co-occurrence matrix
基于分块直方图和共生矩阵的图像检索方法
3.
First, the four classical texture features, including texture energy, texture entropy, texture inertial moment and local texture calmness, are calculated based on the co-occurrence matrix of the i.
该方法先计算图像的灰度共生矩阵,提取能量等纹理特征量,进行初检索,再通过Canny算子提取图像边缘,用投影法计算外边缘在垂直和水平方向上的投影,对初检索结果按形状特征进行二级检索。
3)  HIS gray symbiosis matrix
HIS共生矩阵
4)  Statistics matrix
统计表矩阵
5)  gray level co-occurrence matrix
灰度共生矩阵
1.
Texture Image Retrival Based on Wavelet Decomposition and Gray Level Co-occurrence Matrix;
基于小波分解和灰度共生矩阵的纹理图像检索
2.
Texture segmentation on the scale co-occurrence matrix and gray level co-occurrence matrix;
基于尺度和灰度共生矩阵的纹理图像分割
3.
A Self-adaptable Method to Detect Edge in Images Based on Gray level co-occurrence matrix;
基于灰度共生矩阵的自适应图像边缘检测
6)  GLCM
灰度共生矩阵
1.
Wood Texture Classification and Recognition Based on Spatial GLCM;
基于空间灰度共生矩阵木材纹理分类识别的研究
2.
Research on Building Method of GLCM Suitable to Wood Texture;
适于描述木材纹理的灰度共生矩阵构造方法研究
3.
First,GLCM was used to extract the feature parameters of the wood textures.
首先,应用灰度共生矩阵提取了木材的纹理特征参数;其次,在此特征参数体系下,应用 BP 神经网络对木材纹理进行了分类研究,识别率达89%。
补充资料:分布和特征量统计(见统计分析)


分布和特征量统计(见统计分析)


  fenbu he tezhengliang tongjj分布和特征量统计见统计分析。
  
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