It presents the model and feature of content-based image retrieval system, and then discusses some methods of feature abstraction and similarity measurement based on color, texture and shape.
首先叙述了基于内容的图像检索的系统模型和特点，接着针对颜色、纹理和形状进行了概率特征提取、相似度量等的进一步具体分析讨论。
The obtained 3d model is a scaled version of the original object, and the surface texture is obtained from the image sequence as well.
最后求得该物体的表面纹理以及一个与原物成比例的3d模型。
In order to more effectively make use of local features to restore the noise-infected image, a nonlinear filtering algorithm based on local texture direction probability statistic model was proposed.
为了更有效地利用图像的局部特征恢复被噪声感染的图像，基于图像局部纹理方向概率统计模型，提出一种针对混合噪声的非线性滤波算法。
And we adopted the image division and image compress techniques, carried out the method of construct multiresolution texture model.
采用影像分块和纹理压缩技术，实现了多分辨率影像纹理模型的构造方法。
The fractal Brown function is the stochastic fractal mathematical model that can better reflect the statistic characteristics of image texture.
分形布朗函数是随机分形的数学模型，对于图像纹理所具有的统计特性可以被较好的反映出来。
Seven texture parameters of this model are used for classifying six types of remote sense image over 210 samples. It's success percent is 98. 6 %.
使用本模型的七个纹理参数作特征，在六类地物类型210个样本上作实验，由此设计的分类器的识别率为98.6%。
But all you really need is to copy an image into a block's folder and then it can be loaded as a texture, likewise creating a. Obj model and putting that into a block's folder will load the new model!
但你真正需要的是复制一个图像块的文件夹，然后它可以作为一个纹理加载，同样创造一个。obj模型，将成块的文件夹将加载新模型！
Texture image segmentation is foundation of image analysis, model recognition and computer vision, which is also a classic problem.
纹理分割是图像分析、模式识别、计算机视觉等领域的基础，也是个经典难题。
Using texture mapping method vertically maps the input image to 3D geometric human face model.
采用纹理映射方法把输入图像垂直映射到三维人脸几何模型上。
Texture image interpolated by the novel model preserves the entire texture pattern; the jaggies in linear structure of texture is smoothed too.
使用双层约束模型处理纹理图像可以保持纹理特征，平滑纹理部分线形特征位置的块状效应。
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。
Combined with the active contour image segmentation method, this model can be applied to texture segmentation.
再利用基于活动围道的图像分割算法对该子图像进行分割，可以获得良好的纹理图像分割结果。
And 15 texture parameters are calculated by using this model for each image.
由此模型计算出十五个纹理参数。
This paper presents a novel approach to unsupervised texture segmentation according to a very general nonparametric statistical model of image neighborhoods.
针对基于统计的纹理分割算法存在的不足，提出了一种新的多分辨模型下的无监督统计纹理分割算法。
This paper proposes a texture preserving fourth order partial differential equations based image denoising model.
利用垂直于梯度方向的图像二阶导数设计了一种新的代价函数。
This paper proposes a texture preserving fourth order partial differential equations based image denoising model.
利用垂直于梯度方向的图像二阶导数设计了一种新的代价函数。
应用推荐