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计算机工程

• 图形图像处理 • 上一篇    下一篇

基于跨媒体字典的图像检索

顾文娇1,2,张化祥1,2   

  1. (1. 山东师范大学信息科学与工程学院,济南 250014;2. 山东省分布式计算机软件新技术重点实验室,济南 250014)
  • 收稿日期:2013-05-24 出版日期:2014-06-15 发布日期:2014-06-13
  • 作者简介:顾文娇(1989-),女,硕士研究生,主研方向:图形图像处理,机器学习;张化祥(通讯作者),教授、博士生导师。
  • 基金资助:
    国家自然科学基金资助项目(61170145);教育部博士点基金资助项目(20113704110001);山东省自然科学基金资助项目(ZR2010FM021);山东省科技攻关计划基金资助项目(2013GGX10125);泰山学者基金资助项目。

Image Retrieval Based on Cross-media Dictionary

GU Wen-jiao 1,2, ZHANG Hua-xiang 1,2   

  1. (1. School of Information Science and Engineering, Shandong Normal University, Jinan 250014, China; 2. Shandong Provincial Key Laboratory of Novel Distributed Computer Software Technology, Jinan 250014, China)
  • Received:2013-05-24 Online:2014-06-15 Published:2014-06-13

摘要: 当前存在的图像检索大多是基于内容的检索,为提高检索的准确率,通过整合文本及视觉信息,提出一种自动将文本查询转化为可视化表示的方法,实现基于跨媒体字典的图像检索。采用标注图像集挖掘文本和图像间的关系,训练建立一个类似于双语字典的跨媒体字典,自动将文本查询转化为视觉查询,分别进行基于文本和基于视觉的图像检索,将2种方法检索到的图像合并作为最终检索结果。实验结果表明,该方法能有效地提高图像的查准率。

关键词: 基于内容的图像检索, 跨媒体字典, 文本查询, 可视化表示, 图像标注

Abstract: Nowadays Content-based Image Retrieval(CBIR) is still the most common way of image retrieval. In order to improve the precision, this paper proposes a new approach to image retrieval which explores the integration of textual and visual information. In the process of image retrieval, a technique which automatically transforms textual queries into visual representations is presented. The relationships are mined between texts and images and the relationships are employed to construct a cross-media dictionary to automatically transform textual queries into visual ones. It combines the retrieval results of textual and visual query as the final results. Experimental results show that the proposed approach can effectively improve the image precision.

Key words: Content-based Image Retrieval(CBIR), cross-media dictionary, textual query, visual representation, image annotation

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