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.
Google在2001年发布图像搜索功能时，只有2.5亿索引图像，不到10年，这个巨大的搜索功能已经可以检索超过100亿个图像了，每分钟有35小时的内容上传到YouTube。
When Google launched its image search feature in 2001, it had 250 million indexed images. Less than a decade later, the search giant has indexed over 10 billion images.
运动图像的分割在基于内容的视频编码及视频检索中占有重要的地位。
The segmentation for moving pictures is important in content-based video encoding and video retrieval.
肤色特征在MPEG4、基于内容的图像检索、虚拟现实等领域有着广泛的应用。
The features of skin color are wide used in the areas of MPEG4, content based image retrieve and virtual reality.
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.
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.
最后设计出基于内容的图像浏览与检索系统以验证其有效性和正确性，并给出了系统运行效果示例。
Finally, a content-based image browse and retrieval system are designed to certify its validity and correctness, and the demonstrations of systematic operation result are provided.
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.
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.
因此，如何结合语义特征，使得所抽取的低层物理特征和图像内容所表示的语义特征之间建立良好的联系，实现高效的图像检索，仍是很长一段时间内需要研究解决的问题之一。
Therefore, it is still an unsolved problem about how to integrate with semantic features to achieve better connection between the lower physical features and the image content for efficient retrieval.
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.
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。
This paper presents a color images region growing method based on online learning algorithm, which is used for content-based image retrieval systems.
在基于图像内容的图像检索系统中，搜索引擎检索图像类似于按照相似标准来查询图像。
In content based image retrieval system, search engine retrieves the images similar standard to the Cey words query image according to a similarity measure.
研究了基于内容的图像检索系统中的目标描述模型的建立方法。
In this paper, constructing object description model in content based image retrieval system is focused on.
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.
本文介绍了多媒体信息检索的原理与特点，着重阐述了基于内容的图像检索、视频检索和音频检索技术。
This paper introduces the principle and characteristics of multimedia information retrieval and elucidates content-based multimedia retrieval technology of image, video and audio.
基于内容的图像检索(CBIR)技术的研究主要包括两个方面：可视化特征提取和相似性度量。
The principal research of content based image retrieve (CBIR) includes two aspects: visual feature representation and similarity measurement.
基于内容的多媒体检索，包括图像、音频和视频等信息的检索，本文主要是对基于内容的图像检索进行了研究。
Content Based Multimedia retrieval includes the image, audio and video retrieval, among which this paper does the most research on the image retrieval.
通过使用表象性的视觉信息，对医学图像范畴内的典型图像进行了基于视觉内容的检索实验。
By using the visual presentative information, the visual content based retrieve experiments were made through typical image in domain of medical image.
原型系统证实了新方法的可行性，获得了直接在数字化图像上自动完成古籍内容检索的技术效果。
The operational prototypical system demonstrates its feasibility and gets the effectiveness of automatic content based retrieval directly on page images.
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.
在医学信息领域，对医学图像物理特征的研究有助于实现图像的自动分析和基于内容的检索。
In medical informatics, the study of medical images 'physical features contributes to implement auto analysis and content-based retrieval.
本文介绍了基于内容图像检索的基本原理、检索方式和关键技术，并列举了几种较为先进的图像检索系统。
This paper introduces the basic theory, retrieval mode and critical technology of content-based image retrieval and illustrates some advanced image retrieval systems.
基于内容的图像检索技术依据图像的画面内容特征来检索图像库中与目标图像相似的图像。
The Content-based image retrieval technique search the image in the image library by the content features. The result is similar to the target image.
分形编码在图像压缩方面取得了很好的效果，同时也能够用于基于内容的图像检索。
Fractal coding has been proved useful for image compression, and it is also proved effective for content-based image retrieval.
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.
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.
由于图像数据中普遍存在的“语义鸿沟”问题，传统的基于内容的图像检索技术对于数字图书馆中的图像检索往往力不从心。
Because of the "semantic gap" which is often encountered in the image data, traditional CBIR technology cant deal with the problem of image retrieval in digital libraries sometimes.
由于图像数据中普遍存在的“语义鸿沟”问题，传统的基于内容的图像检索技术对于数字图书馆中的图像检索往往力不从心。
Because of the "semantic gap" which is often encountered in the image data, traditional CBIR technology cant deal with the problem of image retrieval in digital libraries sometimes.
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