| 基于显著点和关键块相结合的图像检索方法 |
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| 引用本文： | 曲晓光,王国宇.基于显著点和关键块相结合的图像检索方法[J].计算机应用,2006,26(3):613-0614. |
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| 作者姓名： | 曲晓光 王国宇 |
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| 作者单位： | 中国海洋大学,信息科学与工程学院,山东,青岛,266071;中国海洋大学,信息科学与工程学院,山东,青岛,266071 |
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| 摘 要： | 提出了一种基于小波变化显著点和基于关键块相结合的图像检索方法。首先利用小波变换提取图像的显著点，然后将图像划分成均匀的图像块，将图像块分为有显著点的和无显著点两类。提取块的低层次特征矢量，将两幅图像之间的匹配转换成图像块之间的匹配。在图像检索时，通过对这两类图像块分别进行相似性度量，对得到的结果加以不同的权重，以实现对图像局部或全局不同要求的检索。
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| 关 键 词： | 基于内容的图像检索 显著点 关键块 聚簇 码书 |
| 文章编号： | 1001-9081（2006）03-0613-02 |
| 收稿时间： | 2005-09-06 |
| 修稿时间： | 2005-09-062005-11-14 |
Image retrieval based on salient points and keyblocks |
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| QU Xiao-guang,WANG Guo-yu.Image retrieval based on salient points and keyblocks[J].journal of Computer Applications,2006,26(3):613-0614. |
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| Authors: | QU Xiao-guang WANG Guo-yu |
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| Affiliation: | College of Information Science and Engineering, Ocean University of China, Qingdao Shandong 266071, China |
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| Abstract: | A novel image retrieval method was proposed based on salient points and keyblocks. First salient points were extracted using wavelet transform, then the image was segmented into equal-size blocks. These blocks could be divided into two classes, one with the salient points and the other not. Low-level features such as color were extracted to describe block. By adjusting the weights of the two classes in image retrieval, different results depending on our interest in local or global similarity could be got. |
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| Keywords: | CBIR(Content-Based Image Retrieval) salient points keyblocks clustering codebook |
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