摘要
提出一种在无标注图像库中进行的基于关键词的检索方法.该方法在用户输入关键词后,首先利用图像周围的文字信息从网页中过滤一部分与检索主题无关的图像.然后利用图像的视觉特征在之前的基础上筛选出与检索词具有高度相关性的图像.最后利用数据审计技术对筛选出的图像进行进一步精化,并利用精化后的图像对图像库进行检索.实验结果表明,借助数据审计技术,该方法可有效提高对无标注图像库进行基于关键词的检索性能.
An approach is proposed for keyword-based image retrieval in unannotated image databases. After the keyword is input, the surrounding text information of the images is used to filter some irrelevant images, and then the visual information is extracted to select the relevant images. The data editing techniques are employed to refine the relevant images which are used as queries for retrieving images from the image databases. Experimental results show that the proposed method can achieve good retrieval performance in unannotated image databases.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2009年第3期422-426,共5页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金项目(No.60505013
60721002)
国家863计划项目(No.2007AA01Z169)资助
