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Novel image retrieval algorithm based on BTC[J]. 引用该论文赵珊;安志勇;周利华.
Extracting the semantics present in images and videos is the difficulty and the key point of images retrieval. 自动抽取图像／视频的语义内容是图像／视频检索中研究的重点和难点。
This paper presents a method of medical images retrieval about sternums based on texture and shape features combining with semantic information. 文章根据胸片图像的特点,提出了一种结合图像纹理、形状和语义信息的胸片图像检索方法。
From experiences, it is obvious that this method is consistent with human vision semanteme, and do well in trademark images retrieval. 试验表明，这种方法符合人的视觉语义，能很好地应用于商标图像检索中。
The paper presents a new content-based image retrieval method. 摘要文中提出了一种新的基于多分辨率直方图的图像样本检索方法。
This paper presented a method of medical images retrieval about sternums based on texture features combining with semantic information. 摘要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。
The thesis is focused on content-based image retrieval (CBIR). 本论文的主要研究内容是基于内容的图像检索。
This paper proposes an image retrieval method based on NMI (Normalized Monent of Inertia) invariable feature for binary trade mark images. 文中针对二值商标图像，提出一种基于NMI特征的商标图像检索方法。
Content-base image retrieval(CBIR) has become an important research. 基于内容的图像检索已经成为图像检索的一个重要研究方向。
So the content-based image retrieval (CBIR) has been widely researched. 因此，基于内容的图像检索(Content-Based Image Retrieval, CBIR) 已成为解决图像检索问题的研究热点。
Text data presented in images and video contains useful and important semantic information for semantic-based image retrieval system. 视频图像中的文本是从语义层次对视频图像内容进行描述的非常有效信息,文本检测为基于语义的图像检索提供了条件。
In our experiments, The MOAB classification coding scheme enables a unique classification of medical images so as to develop further content-based medical image retrieval. 实验表明M以B(以上四组信息的英语首字母)编码能够实现对医学图像进行唯一的分类，而且分类编码的构架灵活，易于扩充。
Content based image retrieval (CBIR) is one of the fields of Multimedia information retrieval.The difficulty of CBIR is to properly express the contents of the images. 基于内容的图像信息检索是多媒体信息检索领域中重要的组成部分,对图像的内容进行准确快速的描述一直都是图像检索技术中研究的重点和难点。
Finally, the Euclidean distance between two images normalized moment vectors gives the measure of similarity, and constructs a shape-based image retrieval system. 最后,对特征向量进行高斯归一化,用欧氏距离度量图像间的相似度,构建了一个基于形状特征的图像检索系统。
Dissertation: An Intelligent Agent Based Spoken Dialogue System for Content-based Image Retrieval. 毕业论文:基于智能体的计算机对话系统及其在基于内容的图像搜索中的应用。
Content-Based Image Retrieval of Butterflies. National Taiwan University, Taipei, Taiwan. 蝴蝶影像内容检索。国立台湾大学资讯工程学研究所硕士论文，台北市。
Content-based image retrieval (CBIR) is an advanced project in the recent research area of multimedia retrieval. 基于内容的图像检索 (CBIR)是多媒体检索研究的前沿课题 .
An image retrieval method based on user selected region of interest was proposed. 摘要提出了一种基于用户选择感兴趣区域的图像检索方法。
Experiments show that MFCM is applied to image retrieval is effective in exactness and real-time property. 实验表明该方法应用于图像检索,在准确性和实时性方面均能达到较好的效果。
The sharp increase of image information makes image retrieval technology develop fast too. 摘要图像信息的急剧增长，使得图像检索技术也获得迅速发展。