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Efficient Image Retrieval Using Conceptualization of Annotated Images

机译:使用注释图像概念化的有效图像检索

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As the amount of visual information is rapidly increasing, users want to find the more semantic information easily. Most retrieval systems by low-level features(such as color, texture) could not satisfy user’s demand. To interpret semantic of image, many researchers use keywords as textual annotation. However, it’s the image retrieval without ranking by text matching which is the simplest way to retrieval according to keyword’s existence or nonexistence. In this paper, we propose conceptualization by similarity measure using relations among keywords for efficient image retrieval. We experiment annotated image retrieval by lowering the unrelated keyword’s weight value and raising important keyword’s one.
机译:随着视觉信息的数量正在迅速增加,用户希望容易地找到更多的语义信息。大多数检索系统通过低级功能(如颜色,纹理)无法满足用户的需求。要解释图像的语义,许多研究人员使用关键字作为文本注释。但是,它是图像检索,无需按文本匹配排列,这是根据关键字的存在或不存在来检索的最简单方法。在本文中,我们使用关键字之间的关系来提出相似性测量的概念化,以便有效图像检索。通过降低不相关的关键字的权重值并培养重要的关键字,我们尝试注释图像检索。

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