在纹理特征提取方面，针对不同纹理特点分别采用了基于共生矩阵的统计纹理分析和基于小波变换的频谱纹理分析两种方法予以实现。
Similarly, the work of texture feature extraction is obtained by using co-occurrence matrix or frequency analysis based on wavelet transform depending on different characteristics of images.
本文在现有的理论和文献基础上，研究了一种基于图像纹理统计特征分析的面部皮肤状态检测系统。
In this paper, depending on available theory and literature, it studied a kind of measuring system of facial skin condition based on statistical feature analysis of image texture.
在使用模板匹配方法检测织物瑕疵的过程中，通过实时采集、分析织物的灰度图像，获得织物纹理的统计信息，并从中提取出正常纹理的特征。
In the detection of fabric flaw based on template matching, statistical information of natural and normal texture of the fabric can be extracted via collecting and analyzing the gray image.
介绍了一种利用局部沃尔什变换(LWT)提取图像纹理特征的新方法，给出lwt的定义，并分析了LWT系数的统计特性及其各阶矩的纹理鉴别性能。
A new texture feature extraction method using Local Walsh Transform (LWT) is presented. The definition of LWT is given. The statistical properties of LWT coefficients are analyzed.
在对图像纹理特征进行统计分析的基础上，本文提出了一种基于纹理分析的图像小波变换清晰度评价方法。
An image definition criterion using wavelet transform based on the texture analysis was proposed in this paper through the statistical analysis to the image texture characteristic.
在对图像纹理特征进行统计分析的基础上，本文提出了一种基于纹理分析的图像小波变换清晰度评价方法。
An image definition criterion using wavelet transform based on the texture analysis was proposed in this paper through the statistical analysis to the image texture characteristic.
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