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浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (12): 2129-2135    DOI: 10.3785/j.issn.1008-973X.2009.12.001
自动化技术、计算机技术     
使用加权图像标注改进Web图像检索
黄鹏,陈纯,王灿,卜佳俊,陈伟,仇光
(浙江大学 浙江省服务机器人重点实验室,计算机科学与技术学院,浙江 杭州 310027)
Improved Web image retrieval by weighted image annotations
HUANG Peng, CHEN Chun, WANG Can, BU Jia-jun, CHEN  Wei, QIU Guang
（Zhejiang Key Laboratory of Service Robot, Zhejiang University, Hangzhou 310027, China）
 全文: PDF(1044 KB)   HTML
摘要：

为了提高Web图像的检索质量,提出了一种融合文本关键字和图像视觉内容的Web图像检索方法.通过改进的图像自动标注模型,将Web图像本身所蕴含的低层视觉特征映射到图像高层语义特征,即图像文本标注；再将词汇相似性计算技术作为语义信息的度量手段,将图像文本标注转换成带有权重的文本标注；利用贝叶斯推理网检索模型内在的多信息融合能力,将带权重的Web图像文本标注特征和Web文档中的文本信息无缝地融合在一起实现Web图像检索.实验结果表明,将Web中的文本关键字和Web图像视觉内容融合起来可在一定程度上提高Web图像检索质量.
Abstract:

A Web image retrieval method was proposed which combines textual terms extracted from Web documents and image contents in order to improve Web image retrieval.  Web  image contents were translated into image annotations by the improved automatic image annotation model. Then the technology of term similarity measurement, as the metric form of  semantic information, was applied to weighting image annotations. These annotations and some terms extracted from Web documents were introduced into Web image retrieval under  the framework of Bayesian  inference network which has an inherent fusion capability of multiple information sources. Experimental results show that the  method improves image  retrieval to some extent by combining Web image contents and terms in Web documents．
出版日期: 2010-01-16
:  TP 391.41  
基金资助:

国家科技支撑计划资助项目（2008BAH26B00） ；浙江省优先主题社会发展资助项目（2007C13019）.
通讯作者: 王灿,男,讲师.     E-mail: wcan@zju.edu.cn
作者简介: 黄鹏（1979-）,男,江西上高人,博士生,从事自然语言处理、图像处理、Web检索研究.
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引用本文:

黄鹏, 陈纯, 王灿, 等. 使用加权图像标注改进Web图像检索[J]. J4, 2009, 43(12): 2129-2135.

HUANG Feng, CHEN Chun, WANG Can, et al. Improved Web image retrieval by weighted image annotations. J4, 2009, 43(12): 2129-2135.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2009.12.001    或    http://www.zjujournals.com/eng/CN/Y2009/V43/I12/2129

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