摘要
基于内容的图像检索研究(Content-based Image Retrieval,CBIR)的目的是实现自动地、智能地检索图像,研究的对象是使查询者可以方便、快速、准确地从图像数据库中查找特定图像的方法和技术。本文在改进传统的相关反馈算法基础上,引入可更新的特征库,可以将用户反馈的信息逐步嵌入到这个可更新特征库中。实验结果证实了本文改进算法的有效性。
The purpose of the research of content - based image retrieval is to realize retrieving images automatically and intelligently. The objects of the research are methods and technology that can help the user retrieve particular images from image database conveniently, quickly and accurately. This thesis improved a conventional relevance feedback algorithm by importing an updatable feature database into the improved algorithm. With this algorithm the system can gradually embed the user＇ s feedback information into the updatable feature database. The results of the experiments show that the method is very efficient.
出处
《计算技术与自动化》
2007年第2期38-41,共4页
Computing Technology and Automation
关键词
图像检索
纹理
特征提取
相似性度量
相关反馈
image retrieval
texture
feature extraction
similarity measure
relevance feedback
