This paper presents a color images region growing method based on online learning algorithm, which is used for content-based image retrieval systems.
论文阐述了一种基于在线学习算法的彩色图像区域增长法，用于解决基于内容的图像检索系统。
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 first part is a kind of store image retrieval base on color. Another is about morphology operators based on rough set theory.
第一部分是基于颜色的记忆性图像检索，另外一部分为基于粗糙集理论的形态学算子。
Experiments demonstrated that the color block co-occurrence matrix descriptor considerably improves the retrieval performance and can combine the feature of color and texture effectively.
实验结果表明，彩色子块共生矩阵描述子能够有效地结合颜色和纹理特征，具有良好的检索性能。
Color quantization is an important method of image retrieval based on color feature.
颜色量化是基于颜色特征的图像检索的一个重要方法。
Based on the first method be proposed in this dissertation, a new method for image retrieval based on local color distribution of salient points is proposed.
在本文提出的第一种方法的基础上，进行进一步的研究改进，提出了基于显著点局部颜色特征空间分布的图像检索方法。
A new image retrieval algorithm based on the main color and shape of image blocks was presented.
提出一种新的基于分块主色和形状特征的图像检索算法。
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.
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。
It is easy to perform for traditional image retrieval based on color histogram, however, its calculation in color histogram intersection is too large and the space distribution information is lost.
传统的基于颜色直方图特征的图象检索方法简单且易于实现，但其直方图求交运算量过大，而且丢失了颜色的空间分布信息。
In order to solve this problem, an image retrieval method based on multiple color space was presented: the pixels in the singular regions were expressed by YUV and the others by HSV.
在此基础上，提出了基于多颜色空间的图像检索方法，奇异区域的像素点用YUV颜色空间表示，其他像素点用HSV颜色空间表示。
In this paper, a new image retrieval algorithm based on color is proposed.
提出了一种新的基于颜色的图像检索算法。
With the confirm of the object region in image, a color image retrieval algorithm based on the main object region of the image is presented.
在图像主目标区域确定的基础上，提出了基于主目标区域的图像颜色特征的综合检索方法。
A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed.
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。
Introduces color feature extraction and matching algorithms in content-based image retrieval, such as weighted Euclidean-distance, weighted centre distance, histogram intersection algorithm, etc.
介绍了基于内容图像检索中多种颜色的特征提取和匹配算法，以及加权欧几里得距离、中心距的加权距离、直方图交集算法等。
Color and shape are common features which were used in the Content Based Image Retrieval System.
颜色和形状都非基于外容的图像检索体解外常常当用的特征。
The radius histogram and Angle histogram of each color blocks are used to compute the similarity of images for image retrieval.
提出一种基于颜色块的半径直方图和角度直方图的图像检索方法。
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.
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.
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。
In this paper, an approach to color-based image retrieval based on histogram combined with color block is proposed.
提出了一种基于颜色直方图与颜色块相结合的图像检索的新方法。
Finally it carries out image retrieval based on multi-feature by combining color component and shape component.
最后，将颜色特征分量与形状特征分量相结合来实现基于多特征的图像检索。
The color spatial distribution density can provide the color spatial distribution information for CBIR(Content Based Image Retrieval).
在基于内容的图像检索中，颜色的空间分布密度能提供颜色在空间的分布信息。
Color histogram is the most usually used method of content-based image retrieval.
颜色直方图法是基于内容的图像检索系统通常采用的方法。
This text puts forward a kind of method of the color coherence vector based retrieval, increasing biggest inspectional accuracy.
本文提出一种基于颜色聚合向量的图像检索方法，极大地提高了检索精度。
The method is more flexible and accurate to describe the color feature of an image and improves the image retrieval precision.
实验结果表明，该方法实现简单，能够更加灵活、准确地描述图像的颜色特征，从而有效提高了图像检索的准确率。
In content-based image retrieval, color features are widely used.
在基于内容的图像检索中，颜色特征已得到广泛应用。
Color space, color quantization and color feature extraction are the main techniques in image retrieval based on color feature.
基于颜色特征的图像检索技术主要包括颜色空间的选择、颜色量化方法及颜色特征的提取。
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.
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。
CBIR is an image retrieval technology, which synthesizes various visual features in digital image, such as color, textual, and shapes features.
基于内容的图像检索是一种利用图像的颜色、纹理、形状等视觉特征进行图像检索的技术。
Content based image retrieval techniques usually use the color histogram of the full image. But this method can't contain the spatial features.
基于内容的图象检索技术一般采用颜色直方图为特征，但是这种方法不能反映空间特性。
Content based image retrieval techniques usually use the color histogram of the full image. But this method can't contain the spatial features.
基于内容的图象检索技术一般采用颜色直方图为特征，但是这种方法不能反映空间特性。
应用推荐