形状特征提取和表示是基于内容图像检索的重要研究内容之一。
Shape feature extraction and description are one of important research topics in content-based image retrieval.
图片自动语义标注是基于内容图像检索中很重要且很有挑战性的工作。
Automatic linguistic indexing of pictures is an important but highly challenging problem for researchers in content-based image retrieval.
Picitup是世界上领先的基于内容的图像检索服务的web3.0开发者和服务者。
Picitup is a leading web 3.0 developer and provider of content based image search services.
基于内容的图像检索技术是当前多媒体数据库系统和数字图书馆研究中的一个热点。
Contentbased image retrieval is a hotspot in the research of multimedia database system and digital library.
多维索引技术是基于内容检索的图像数据库的关键技术。
Multidimensional indexing technology is the key technology of content-based retrieval in image database.
基于内容的图像检索技术是当今研究的热点领域之一。
The image search technique based on content becomes a hot research topic.
基于内容的图像数据库检索技术是当今的一个研究热点，国内外的许多研究机构都在从事这一课题的研究，并取得了一定的研究成果。
The retrieval technique of content-based image database is a focus of query technology studying nowadays, many institutes being engaged in this project have obtained some achievements home and abroad.
基于内容的图像数据库检索技术是当今的一个研究热点。
The retrieval technique of content-based image database is a focus of query technology studying nowadays.
图像检索技术是多媒体应用中的关键技术，现有的基于内容的图像检索技术大都是基于非压缩域的。
Image retrieval techniques are crucial in multimedia application, a number of retrieval techniques that operate in the pixel domain have been reported in the literature.
基于内容的图像检索技术是利用计算机图像处理和数据库管理系统，把图像的可视特征作为数据库检索的依据，对图像数据库进行近似检索。
Based on image Processing and database Management System, Content Based image Retrieval (CBIR) is employed to obtain approximate results from image database, using the visual feature of images.
基于内容的图像检索是根据描述图像视觉内容的特征向量进行相似性检索，其中图像视觉内容的提取可以是通用的，也可以是基于特定领域的。
Content based image retrieval is to perform the similarity retrieval according to the image features representing the image content, which may be extracted in the generic or specific domain.
低层视觉特征提取、高维数据索引机制和相关反馈方法是面向大规模图像库基于内容检索的三个关键问题。
Visional feature extraction, high dimensional indexing mechanism and relevance feedback are three important issues in content-based image retrieval.
近年来，基于内容的图像检索系统(CBIR)是一个热门的研究话题。
In recent years, the content-based image retrieval (CBIR) system is a hot research topic.
基于内容的图像检索系统涉及许多方面关键技术，如何准确有效的表示图像内容是其中的核心问题。
The key technologies of content-based image retrieval (CBIR) system contain a lot of aspects. The most important point is how to represent multimedia content accurately and completely.
基于内容的多媒体信息检索是当前世界的研究热点，然而在图像内容表示及其相似性度量这两个关键问题上取得的进展还不能令人满意。
Content based image retrieval (CBIR) has been an active research area, however, the achievements in image representation and similarity measurement are not satisfying.
如何实现特大图像基于内容的检索是航测、遥感和卫星图像等应用中的关键问题之一。
It is one of the key problems for the application of aerial, remote sensing and satellite images how to retrieve super large image quickly.
传统的以浮点矢量形式表示的图像特征，是基于内容的图像检索技术的基础。
The traditional float vector based image feature is the base of content based image retrieval techniques.
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。
Color histogram is the most usually used method of content-based image retrieval.
有效的高维索引机制是基于内容的图像检索的关键技术，具有重要的理论意义和应用价值。
Efficient indexing schemes for high-dimensional data are important for Content-Based Image Retrieval, with theoretical and applicable value as result.
基于内容的图像检索是当前图像数据库领域的一个研究热点。
Content Based image Retrieval is an important and fascinating point of the image database.
图像检索是有着广泛意义的多媒体应用领域。基于内容的图像检索属于较高层次上的检索。
Image retrieval is an applicable field of the multimedia technology, which is wide in scope.
如何有效准确的表达图像特征是基于内容的图像检索技术的核心问题。
How to describe image characters efficiently and accurately is a core problem in CBIR.
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。
CBIR is an image retrieval technology, which synthesizes various visual features in digital image, such as color, textual, and shapes features.
这两种方法既能够反映全局特征，又能够兼顾所感兴趣区域的局部特征，是基于内容的图像检索的两种非常有效的方法。
At the same time those two methods can reflect global feature and regions-of-interest feature. At the same time those a…
这两种方法既能够反映全局特征，又能够兼顾所感兴趣区域的局部特征，是基于内容的图像检索的两种非常有效的方法。
At the same time those two methods can reflect global feature and regions-of-interest feature. At the same time those a…
应用推荐