针对基本轮廓波变换纹理检索系统检索率较低的问题，提出了一种无下采样轮廓波变换（NSCT）纹理图像检索系统。
Referring to the low retrieval rate of basic contourlet transform, a Non-subsampled Contourlet Transform (NSCT) texture image retrieval system is proposed.
纹理特征作为基本的视觉特征之一，在基于内容的遥感图像检索中得到了广泛的应用。
As one of the fundamental visualized characters, texture feature is used widely in the Content-based Remote Sensing Images Retrieval.
针对离散小波变换具有平移变化性和弱方向性的特性，本文提出了一种基于双树复小波变换(DT- CWT)统计模型的医学图像纹理检索方法。
Presents a novel texture retrieval approach of medical images based on statistic model by Dual-Tree Complex Wavelet Trans - form (DT-CWT) for the shift sensitivity and poor directionality of DWT.
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。
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.
提出了一种结合颜色、纹理和形状特征的细胞病理图像检索方法。
A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed.
该方法在DCT压缩域，通过直接对DCT系数计算，获得图像纹理的统计特征，并作为检索的依据。
The statistical features of the texture images is computed directly from DCT coefficients, and used for image retrieval.
该文实现了一个实用基于颜色、纹理特征的图像检索系统。
This thesis presents a practical image retrieving system based on color and texture characteristic.
纹理是图像的重要属性，基于纹理特征检索图像是当前的研究热点，对图像的纹理进行相似性比较是进行图像检索的关键。
Texture is an important item of image information, texture-based image retrieval has been an active research area, and the similarity comparison of texture features is a key to image retrieval.
该文以花边图像为例，对基于形状和纹理特征的检索方法进行了比较研究，取得了令人满意的实验结果。
In this paper, the retrieval approaches using the shape and texture features of lacework are studied and some encouraging experimental results are got.
提出一种结合图像分块纹理特征和语义信息的医学胸片图像检索方法。
This paper presented a method of medical images retrieval about sternums based on texture features combining with semantic information.
在检索中，颜色和纹理特征的权重不同，本文采用线性加权方式综合颜色特征相似距离和纹理特征相似距离，对图像进行检索。
In this paper, we using a kind of comprehensive image retrieval which fuses color and texture features by linear weights and discuss the method which the weights are determined.
提出了一种基于颜色和纹理特征的图像检索方法。
A novel image retrieval method based on color and texture feature is proposed.
在此基础上，采用一种改进的基于纹理基元的共生矩阵来获取纹理特征，并结合纹理基元的形状直方图来进行图像检索。
On the basis of which, an improved co-occurrence matrix and histogram are developed to extract the texture and shape features for the image retrieval.
本文介绍了我们设计的分别基于颜色特征和基于纹理特征的两种图像检索算法。
In this paper, our methods for image retrieval using color and texture features are first discussed.
本文主要对基于纹理的图像检索技术进行了深入研究。
The texture-based image retrieval technology is deeply studied in this paper.
针对图像中常见的旋转问题提出一种旋转不变纹理特征进行两级图像检索的方法。
A method used for two-stage image retrieval with rotation-invariant texture feature is proposed against the common rotation problem of image.
结合鱼病图像的实际，本文研究并实现了用形状特征、颜色特征和纹理特征分别进行基于内容的图像检索方法。
Considering the fact of the ill fish image, the paper researched and presented the algorithm of content based image retrieval that was according to the represent shape, color or vein in image.
提出利用最大相关最小距离将图像的纹理特征、高斯密度特征与人脸检测相结合的算法进行图像检索。
A new image retrieval method by using Max correlation min distance to combine together texture features, Gaussian density characteristics and face detection of images for image retrieval is presented.
传统的图像检索主要依赖颜色、纹理、形状、空间关系等单一视觉特征，检索效果往往不够理想。
Traditional image retrieval methods is mainly dependent on the single vision features such as color texture shape and so on. So its retrieval result is not always ideal.
提出了一种针对多纹理图像的基于轮廓和纹理分割的检索策略。
Firstly, the contour of each texture primitive is extracted from an image and its Fourier descriptor is calculated.
传统的图像检索主要依赖颜色、纹理、形状、空间关系等单一视觉特征，检索效果往往不够理想。
Traditional image retrieval methods is mainly dependent on the single vision features such as color Grain shape and so on, so its retrieval result always not ideally.
由于综合利用了图像的颜色及纹理特征，实验结果表明，该方法取得了较好的检索效果。
Experimental results show that the new method is efficient and it provides noticeable improvement to the performance of image retrieval.
对真实图像检索的实验表明，本文的方法对于纹理图像的检索具有很好的检索效果。
After experimented for true images, the better achievement is obtained when retrieving texture images by our approaches.
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。
Nowadays, texture image analysis and classification is widely used in blemish locate, object recognize, image search, remote sensing image analysis and other fields.
首先运用灰度共生矩阵提取图像的纹理特征，然后用EBP - OP算法对提取的纹理特征进行分类，并在此基础上实现一组纹理图像的检索，实验证明这种方法是有效的。
First selects texture features based on the gray level co-occurrence Matrix and then EBP-OP neural network is used as a classifier. The experimental results show that this method is very effective.
传统的基于内容的图像检索主要依赖颜色、纹理、形状、空间关系等单一视觉特征，检索效果往往不够理想。
Traditionally image retrieval mainly relies on single feature such as color, texture, shape and spatial relationship, etc., so the result is usually not so good.
基于内容检索技术中必不可少的关键步骤就是图像特征的提取，其中可提取的特征有颜色、纹理和形状等。
Among the contend-based retrieval technologies, feature extraction is most important. For instance, color, texture and shape feature etc.
在总结和分析共生矩阵算法的基础上，提出了一个快速获取目标图像纹理特征，进而实现图像检索的方法。
Base on generalization and analysis of co-occurrence matrix algorithms, a method is proposed that could make fast acquisition of target image texture features and thus implement image retrieval.
提出使用多尺度复杂性方法和多尺度分维数方法提取医学图像纹理特征并将之用于图像检索。
To extract texture features from medical images, the approaches for multi-scale complexity and multi-scale fractal dimension were proposed in this paper.
基于内容的图像检索技术主要利用图像的颜色、纹理和形状特征对图像进行检索，论文重点研究基于颜色和纹理特征的图像检索技术。
The main features used for image retrieval are color, texture and shape. This thesis looks into image retrieval techniques based on color and texture.
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