The contents in the paper include acoustic image preprocessing, feature extraction of texture and shape, and classifier design.
内容涉及声图像的预处理、纹理和形状特征的提取，以及分类器的设计等。
The key technique include skin color detection, skin texture analysis, object area segmentation, image features extraction and the design of classifier.
肤色检测、皮肤的纹理分析检测、目标区域的分割、图像特征的提取、分类器的设计。
The description and extraction of SAR image texture feature is important to texture segmentation.
SAR图像纹理特征的描述和提取是纹理分割的关键。
Accordingly, we propose an improved feature extraction scheme, adopting the tone of filtered image combined with the texture features based on the GLCM of unfiltered image to form the feature vector.
针对这种情况，提出了一种改进的特征提取方法，将基于原图像的灰度级共生矩阵提取的纹理特征与滤波后图像的灰度特征进行组合用于分类。
The techniques for realization of OWT and applications in image feature extraction and texture segmentation are explored thoroughly.
深入研究了光学子波变换的实现技术及其在图象特征提取和纹理图象分割等方面的应用。
Efficient extraction of image texture features are used on the following support vector machine classifier learning and training have a very important role.
图像纹理特征的有效提取对下面所用到的支持向量机分类器来进行学习和训练有非常重要的作用。
Finally, based on the work of above, proposed a method of description and extraction image color and texture features in the dual tree complex wavelet transformation domain.
最后，在上面工作的基础上，提出了基于对偶数复小波域的图像的颜色和纹理特征的描述和提取方法。
This paper proposes a fast algorithm for texture feature extraction. The new algorithm is suitable for remote image classification on line.
给出一种抽取纹理特征的算法，该算法实时性强，适于在线遥感图像分类。
Likewise, granular computing theory is trying to apply to texture features extraction and accurate segmentation of chest HRCT image.
同样，粒计算理论也在被尝试应用于HRCT图像纹理特征值提取和肺部组织分割。
A nature scene image color-texture feature extraction method based on human visual system (HVS) was proposed.
提出了基于人类视觉系统的自然场景图像颜色和纹理特征提取方法。
In this method, the SVM classification model combined with texture analysis is established on the basis of texture extraction from SPOT5 remote sensing image.
该方法在对SPOT5遥感影像进行纹理特征提取的基础上，构建了结合多窗口纹理的SVM模型。
Then, land cover classification and residential areas extraction with combined texture feature was proposed by the sufficient analysis of the texture feature with different image window.
然后在充分分析影像不同窗口纹理特征的基础上，提出应用组合纹理特征进行土地覆盖分类和居民地信息提取方法。
Then, land cover classification and residential areas extraction with combined texture feature was proposed by the sufficient analysis of the texture feature with different image window.
然后在充分分析影像不同窗口纹理特征的基础上，提出应用组合纹理特征进行土地覆盖分类和居民地信息提取方法。
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