1) gray level-gradient cooccurrent matrix
灰度梯度共生矩阵
2) gray level-gradient co-occurrence matrix
灰度-梯度共生矩阵
1.
According to the characteristics of the timber surface defect,we present an automatic technique for thresholding of timber surface defect images based on gray level-gradient co-occurrence matrix and the maximum entropy principle.
根据木材表面缺陷图像的特点,提出了基于灰度-梯度共生矩阵模型和最大熵原理的木材缺陷图像自动阀值化技术。
2.
Entropy thresholding method is an automatic technique for thresholding of digital images based on gray level-gradient co-occurrence matrix and the maximum entropy principle.
它包括二维匹配滤波预处理以增强血管的灰度,以及用灰度-梯度共生矩阵的最大熵阈值化方法。
3) gray-gradient co-occurrence matrix
灰度-梯度共生矩阵
1.
The gray-gradient co-occurrence matrix of the text region is calculated,and the optimum thresholds of segmented grayscale and gradient are found quickly according to the objective function.
首先计算文本区域的灰度-梯度共生矩阵,并根据目标函数快速地找到分割的灰度和梯度最佳阈值;然后在此基础上提取特征向量,送入神经网络进行分类;最后根据颜色极性判断的结果,分割出字符。
4) gray-grads conjugate matrix
灰度-梯度共轭矩阵
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：不共生
【不共生】
谓六根六尘和合名之为共。前云不自生，则是根不能生；又云不他生，则是尘不能生。根尘各各既不能生，根尘相共又焉得生，故名不共生。
谓六根六尘和合名之为共。前云不自生，则是根不能生；又云不他生，则是尘不能生。根尘各各既不能生，根尘相共又焉得生，故名不共生。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条