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huidu
- 灰度共生矩阵提取纹理特征可用于图像纹理特征提取-GLCM texture
grayfeature
- 使用灰度共生矩阵提取图像的纹理特征，通过提取的特征来表示一副图像，最终每幅图像被表示为51维的一维向量。-Use GLCM texture features extracted image feature extraction is represented by an image, and ultimately each image is represented as a one-dimensional vector of 51 dimensions.
GLCMhePSI
- 图像纹理特征提取算法：灰度共生矩阵、像元形状指数-Texture feature extraction algorithm: GLCM, pixel shape index. .
Liver-CT-Image
- 提出了一种改进的灰度共生矩阵肝脏CT 图纹理特征分析方法，即首先确定图像ROI 区域，接着构造一个新的能综合反映共生矩阵各角度信息的灰度共生矩阵，然后提取基于该矩阵的纹理特征参数。通过实验验证，上述方法是分析肝脏CT 图的一种快速有效的纹理特征分析方法，对其他特定类别图像的纹理特征分析有参考意义。Radon 变换检测航迹, 并对结果进行了优化. 与现有的检测方法相比, 该方法针对性强, 复杂度低. 使用该方法对实际航拍图片进行了检测实验, 取得了很好的效果.-Track propose a no
huidugongsheng
- 介绍了纹理的定义及特征, 并分别对统计方法、结构分析方法、基于纹理模型的方法和信号处理方法四种纹理图像分析方法进行了描述。针对统计方法中的灰度共生矩阵进行了详细的分析研究, 并得到利用其进行纹理分析设计的重要参数。说明灰度共生矩阵法在纹理分析中的重要性-Introduces the definition and characteristics of texture, and were on statistical methods, structural analysis, texture mod
comatrix
- 遥感图像基于灰度共生矩阵的纹理特征统计，用matlab-Texture feature of remote sensing images based on gray level co-occurrence matrix
Texture-feature-extraction
- 由灰度共生矩阵提取常用特征，实现对图像纹理特征的分析-Extracted from the GLCM common characteristics, to achieve image texture features analysis
wenlitezhneg
- 基于灰度共生矩阵的纹理特征提取 用Matlab仿真实现-based on GLCM
bp_network
- 对两种类型的纹理图像，各选取30幅，计算灰度共生矩阵，提取特征向量；构件BP神经网络分类器，用每种类型的前20幅对分类器进行训练，后10幅用来测试分类效果。-Two types of texture image for each select 30 calculated GLCM, extracting feature vectors member BP neural network classifier, before use each type of 20 pairs classifier
GLCM
- 灰度共生矩阵 提取纹理特征 vc6.0 -GLCM texture feature extraction
GLMCandLBPextraction
- 第一个程序提取了图像灰度级为64的灰度共生矩阵，并计算了能量，熵，对比度，相关性，逆差矩这5个参数.第二个程序可以提取彩色图像的LBP纹理特征，可以提取采样点为8、16、24的统一模式（u2）、旋转不变模式（ri）、统一旋转不变模式（riu2）的LBP值。-The first program to extract a grayscale image GLCM 64, and calculate the energy, entropy, contrast, correlation, inverse
ConsoleApp_texture
- 利用灰度共生矩阵提取图像纹理特征的一种算法实现。-An algorithm using gray level co-occurrence matrix of image texture feature extraction.
Texture
- 图像基于统计的纹理特征，包括灰度分布统计，灰度共生矩阵属性。可用于纹理特征提取-Image texture features based on statistics, including the gray distribution statistics, GLCM property. Can be used for texture feature extraction
image-texture-features
- 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。
Texture
- 基于灰度共生矩阵的图像纹理特征提取，所采用的默认为灰度图像，提取了0 45 90 135四个矩阵-texture feature based GLCM
GLCM
- 计算图像的灰度共生矩阵，并基于该矩阵得到14个纹理特征-feature extraction based on GLCM
texture-feature
- 从图片中提取四种不同纹理特征，包括gabor、灰度共生矩阵、灰度直方图、灰度梯度共生矩阵纹理特征。-Four different texture features extracted the image, including gabor, GLCM, histogram, GGCM texture.
glcm24
- Matlab实现灰度共生矩阵算法，0,45,90,135四个方向的，每个方向各6个特征，因而一幅图像总共24个特征。在图像纹理识别方面挺有效。-Matlab implementation of the gray level co-occurrence matrix algorithm, 0,45,90135 four directions, each direction of the 6 characteristics, and thus a total of 24 images of the
GLCM
- opencv实现灰度共生矩阵并求图像的几个纹理特征-opencv glcm实现灰度共生矩阵并求图像的几个纹理特征
GMCL1
- opencv基于纹理特征提取的灰度共生矩阵，效果还比错 可以参考-Opencv based texture feature extraction of the gray level co-occurrence matrix, the effect is also better than the wrong reference