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。
An algorithm of license plate location based on line scanning is proposed according to the abundant texture features in the domain of vehicle license plate.
针对车牌区域内字符串具有丰富的纹理特征，本文提出了一种基于行扫描的车牌定位算法。
A new minutiae verification method based on the fuzzy geometry features and texture features is proposed.
提出了一种新的基于模糊几何特征和纹理特征的细节点验证方法。
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。
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。
An effective method for image segmentation based on color and texture features is proposed.
文章提出了一种有效的基于颜色和纹理综合特征的图像分割方法。
This paper presented a method of medical images retrieval about sternums based on texture features combining with semantic information.
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。
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.
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。
A new method based on least squares and region segmentation is proposed to retrieve and compare the texture features of multi-spectral images in this paper.
该文提出一种基于最小二乘及区域分割的多光谱图像纹理特征提取与比较的方法。
Number Plate location: a location scheme based on the texture features of characters is proposed.
车牌定位部分提出了一种基于字符垂直边缘纹理特征的车牌定位法。
This paper proposes a method for objects extraction based on high and color texture features.
提出一种基于高度和彩色纹理信息的目标识别方法，其目的是提取具有相对高度的地物。
A new group of texture features based on Generalized Local Walsh Transform (GLWT) are presented in this paper.
该文提出一组基于广义局部沃尔什变换(GLWT)的纹理特征。
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.
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。
In the location module, combing with edge and texture features of license plate, in the gray-scale images, a fast location method based on mathematical morphology is proposed.
在定位模块，结合车牌的边缘特征和纹理特征，在灰度图像的基础上，提出了基于数学形态学的车牌快速定位方法。
The feature vector is composed of wavelet texture energy features, texture features based on the gray-level co-occurrence matrix and the tone of filtered SAR image by using tree wavelet.
该方法将树型小波中颇纹理能量特征、灰度共生矩阵特征、树型小波滤波后的灰度组成的特征矢量对SAR图像进行分类。
There are mainly three distinguishing features in our proposed algorithm:local direction-based prediction, extended context for micro texture and histogram initialization based on imaging apparatus.
该算法主要包括三个特色技术：基于纹线局部走向的分类预测、体现指纹微观纹理的扩展上下文以及基于成像仪器的分类熵编码器概率模型初始化。
Firstly, texture and shape features are extracted at the pixel level, and spectral features are extracted at the object level based on multi-scale image segmentation maps.
首先在画素级上提取影像的纹理和形状结构特征，在构建的多尺度分割集影像上提取物件的区域光谱特征。
The main features used for image retrieval are color, texture and shape. This thesis looks into image retrieval techniques based on color and texture.
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 method based on the multidirectional edge detection uses the position, gray, size, direction and relativity of texture, so the dividing features ensure to increase the precision much more.
基于多方向纹理边缘检测的特征提取方法利用了纹理的位置、灰度、大小、方向、相关性等多种结构特征，因此提取出来的可区分性特征使虹膜识别的准确性得到大幅度的提高。
The method based on the multidirectional edge detection uses the position, gray, size, direction and relativity of texture, so the dividing features ensure to increase the precision much more.
基于多方向纹理边缘检测的特征提取方法利用了纹理的位置、灰度、大小、方向、相关性等多种结构特征，因此提取出来的可区分性特征使虹膜识别的准确性得到大幅度的提高。
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