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灰度共生矩阵提取纹理特征
- 灰度共生矩阵提取纹理特征
ResearchonBuildingMethodofGLCM
- 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
GLCM
- 基于灰度共生矩阵的纹理特征提取实现算法,开发平台是vc-GLCM-based texture feature extraction algorithms to achieve
wenli
- 分析了纹理特征提取方法,特别是灰度共生矩阵的方法和 Gabo:小波矩的方法。并在这两种方法的基础上提出了综合灰度共生矩阵和 Gbaor小波矩的纹理特征提取方法并用于图像检索。 -matlab
87361011graycomatrix
- 这是基于灰度共生矩阵提取纹理特征重要参数的代码-This is based on gray level co-occurrence matrix texture features extracted the important parameters of the code
ResearchonComputationofGLCMofImageTexture
- 图像的灰度共生矩阵(GLCM)已知被理论证明并且实验显示它在纹理分析中是一个很好的方法,广泛 用于将灰度值转化为纹理信息. 然而,由于GLCM是像素距离和角度的矩阵函数,因此完整的GLCM的计算,其参数的 选取范围很广,这样GLCM的计算量很大,通常是不能这样用的. 为了解决这个问题,本文应用马尔可夫链的性质,从 理论上证明了GLCM的计算结果,当像素距离足够大的时候趋于一致性. 这样只需较少的参数值就可以完整的描述图 像的纹理特征. 最后,通过对Brodatz纹理库中自然纹理
TuXiangShiBie
- 该软件需用Delphi7设计,采用灰度共生矩阵的方法对肝脏超声图像进行纹理特征提取。通过神经网络进行分类处理。-The software required Delphi7 design, the use of gray-scale co-occurrence matrix method of liver ultrasound image texture feature extraction. Through the neural network classification.
Texture
- 计算灰度共生矩阵的Matlab程序,参考《基于颜色空间和纹理特征的图像检索》,输入图像数据,返回八维纹理特征行向量-A programm computing GLCM texture measurements.
33753125vc_dib
- :为使灰度共生矩阵(GI CM)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 实验结果对优化灰度共生矩阵的构造、实现基于纹理的图像 检索有参考意义。 -gray
wenli
- 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
Texture
- 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.
texturefeature
- 特征提取、 纹理分析、灰度共生矩阵、纹理特征-Feature extraction, texture analysis, gray level co-occurrence matrix, texture features
29782213gray
- 这是基于灰度共生矩阵提取图像纹理特征参数的方法-This is based on GLCM texture feature parameter extraction method of image
31767649image_texture_analysis
- 这是基于灰度共生矩阵的纹理特征重要参数提取的代码-This is based on gray level co-occurrence matrix texture features of the important parameters of the code extraction
81404598texture4
- 这是基于灰度共生矩阵提取纹理特征重要参数的代码-This is based on gray level co-occurrence matrix texture features extracted the important parameters of the code
dx-4.4.4.tar
- 图像的纹理特征参数的灰度共生矩阵的计算,该方法效果好,速度快,易理解。-The image texture characteristic parameters GLCM calculation, the method effective, fast, easy to understand.
texture_GUI
- 此程序是基于灰度共生矩阵的图像纹理特征提取算法,它进行了四个方向上的灰度共生矩阵的计算,从而得出他们的纹理特征向量,再求均值,使计算进度大幅度提高-This program is based on the GLCM texture feature extraction algorithm, which was four directions GLCM calculation to arrive at their texture feature vector, and then seek mean
4
- 4基于灰度共生矩阵纹理特征的SAR图像分割 4 the SAR image segmentation based on gray level co-occurrence matrix texture feature(4 the SAR image segmentation based on gray level co-occurrence matrix texture feature)
4
- 基于灰度共生矩阵纹理特征的SAR图像分割 the SAR image segmentation based on gray level co-occurrence matrix texture feature(the SAR image segmentation based on gray level co-occurrence matrix texture feature)
灰度共生矩阵
- 灰度共生矩阵,指的是一种通过研究灰度的空间相关特性来描述纹理的常用方法。 [1] 1973年Haralick等人提出了用灰度共生矩阵来描述纹理特征。 由于纹理是由灰度分布在空间位置上反复出现而形成的,因而在图像空间中相隔某距离的两像素之间会存在一定的灰度关系,即图像中灰度的空间相关特性。(Gray-level co-occurrence matrix refers to a common method for describing texture by studying the spatia