基于ROI与MCS的图像检索方法  

Image Retrieval Method Based on ROI and MCS

作　　者：郝红卫[1] 黄芳益[1] 周静[1] 

机构地区：[1]北京科技大学信息工程学院,北京100083

出　　处：《模式识别与人工智能》2008年第2期240-245,共6页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金资助项目(No.60675006)

摘　　要：由于目前还没有语义级的目标区域提取算法,致使难以准确提取表达用户检索意图的图像区域,而只提取图像单个特征往往不能满足各种检索需求.针对此,本文引入用户选择感兴趣区域(ROI)和多分类器系统(MCS),先由用户选择感兴趣区域,然后提取所选区域的多种特征,分别构造相应的分类器,最后通过对各分类器结果的集成得到检索结果.实验结果表明,本文方法能够准确获取用户的查询意图,具有更高的查准率.Since there is no effective algorithm for semantic level region extraction, it is difficult to obtain the region that reveals users＇ retrieval purposes exactly. Besides, different retrieval purposes demand various features. In order to solve these problems, an image retrieval method is proposed based on region of interest （ROD and multiple classifier systems （MCS）. Firstly, ROI is selected by users. Then, different features of ROI are extracted for constructing corresponding classifiers. Finally, the retrieval results are obtained by combining the outputs of individual classifiers. Experimental results show that the proposed method can exactly grasp the retrieval users＇ purpose and greatly improve the precision of retrieval systems.

关 键 词：基于内容的图像检索 感兴趣区域(ROD 多分类器系统(MCS) 查准率 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]