The texture classification is completed with back propagation (BP) neural network.
最后利用反向传播(BP)神经网络进行纹理的分类识别。
This paper presents a texture classification approach based on function link network.
提出了一种基于函数联接的感知器神经网络的纹理分类方法。
This paper deals with markov random field and it's application in image texture classification.
针对马尔可夫随机场方法用于影像纹理分类进行了探讨。
This paper puts forward a new method of invariant texture classification for remote sensing image.
本文提出了一种遥感图像旋转不变纹理分类的新方法。
Based on frequency domain distribution and scale feature of textural information, we can do texture classification effectively.
该算法利用纹理信息的频域分布以及尺度特性，并在此基础上进行纹理分类。
In order to detect ship targets under complex sea background, the high-order fractal feature and its application to texture classification are analyzed.
将高阶分形特征用于海面运动目标检测，提取出用于区分运动目标和海杂波的新的分形特征——缝隙特征。
This method is compared with other rotation invariant texture classification algorithm, the experiment results show that it can improve the classification rate effectively.
将该方法与其它旋转不变纹理分类算法进行比较，实验结果表明，提出的算法能有效地提高正确分类率。
This paper used three kinds of texture classification methods to classify aerial image. Through experiment and analysis, we get some Suggestions for choosing texture classification method.
通过对结果的分析得到一些结论，这些结论对于选用和搭配影像纹理分类方法有一定的指导作用。
This paper discusses the shortage of conventional algorithms of texture classification based on wavelet transform, presents two improved approaches of point feature weighting and smart windows.
在基于小波的纹理分类算法的基础上，提出了逐点特征加权和活动窗口算法，使小波纹理分析能够用于高分辨率遥感影像的分类。
A method using two wavelet transform to get the texture feature for remote sensing is put forward, in order to turn out the invariant texture classification for remote sensing in the wavelet domain.
分析了有限脊小波变换可以实现图像的旋转不变性和平移不变性，提出了结合两种小波变换提取图像纹理特征的方法，实现了在小波域中进行图像的不变纹理分类。
Texture and structure of igneous rocks and classification.
岩浆岩的结构和构造岩浆岩的分类。
Key points: texture, structure and classification of sedimentary rocks.
重点：沉积岩的结构、构造和分类。
Key points: texture, structure and classification of igneous rocks.
重点：岩浆岩的分类、结构和构造。
The simplest basis for classification is in terms of structure or texture.
最简单的分类基础是结构或构造。
At first, extracting features of chromaticity moments of texture image of grape disease is done, then classification method of SVM for recognition of grape disease is discussed.
首先利用色度矩提取葡萄病害叶片纹理图像的特征向量，然后将支持向量机分类方法应用于病害的识别。
This paper introduced a method availing autocorrelation functions to estimate the image fractal dimension, and the method can detect classification of the wood texture.
介绍了一种利用自相关函数来估算图像分形维数的方法，并将其应用到木材的纹理分类检测中。
At first, the extracting features of chromaticity moments of texture image of maize disease is done, then classification method of SVM for recognition of maize disease is discussed.
首先利用色度矩提取玉米病害叶片纹理图像的特征向量，然后将支持向量机分类方法应用于病害的识别。
Extracting effective features for texture description and classification is always a difficult problem in texture analysis.
提取有效的特征用于纹理描述和分类一直是纹理分析的难点。
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。
Appropriate texture features are selected with this method to serve image classification and simulative results are discussed.
使用这一方法挑选合适的纹理特征用于图像分类，并对结果进行分析。
Texture analysis has become an important means for improving the accuracy of remote sensing image classification.
纹理分析是提高遥感影像分类精度的重要手段之一。
Nowadays, texture image analysis and classification is widely used in blemish locate, object recognize, image search, remote sensing image analysis and other fields.
现在对于纹理图像的分析和分类广泛用于瑕疵定位、景物识别、图像检索、遥感图像分析等多个领域。
A detection and classification technique for the apple surface texture based on the machine vision was proposed.
提出了一种基于机器视觉技术的苹果表面纹理检测分级方法。
The texture image classification experiments are given to verify the effectiveness of the multi resolutional binomial distribution filter.
在对纹理图象的分类中其性能得到验证。
It is concluded that the fusion of high spatial imagery and multi-spectral bands can enhance change information, and the fusion of texture character can improve the classification results.
通过高几何分辨率图像与多光谱波段融合方法可以，增强变化信息，纹理特征参与变化信息提取可以提高变化类型的分类精度。
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。
The range image is abstracted from the original data and then the height texture is used for assisting classification.
介绍了一种基于点云数据生成距离影像，而后引入对比度纹理辅助的点云数据建筑物快速提取方法。
This paper discusses the optimization of back propagaton neural networks for the grain texture feature, extraction in grain classification.
主要讨论了在谷物纹理识别中对神经网络的优化。
The results show that the split-and-expand algorithm can effectively segment texture images, and its precision of classification is superior to that of the split-and-merge algorithm.
实验结果表明，分开-扩张方法能有效地分割纹理图像，其分割精度优于分开合并方法。
The results show that the split-and-expand algorithm can effectively segment texture images, and its precision of classification is superior to that of the split-and-merge algorithm.
实验结果表明，分开-扩张方法能有效地分割纹理图像，其分割精度优于分开合并方法。
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