%0 Journal Article
%T Using Frequent Pattern Mining for Image Labeling<br>利用频繁模式挖掘进行图像标注
%A ZHOU Xiang
%A ZHOU Xiang-Dong
%A ZHOU Hao-Feng
%A WANG Zhi-Hui
%A WANG Wei
%A SHI Bai-Le
%A <br>周祥
%A 周向东
%A 周浩峰
%A 王智慧
%A 汪卫
%A 施伯乐
%J 计算机科学
%D 2007
%I 
%X One major challenge in the content-based image retrieval and computer vision research is to relate low-level visual features with semantic concepts, that is, to extract semantic concepts from an image effectively according to its low-level visual features. Especially when images contain more than one concept, the problem will be even more intractable. In this paper, we provide a method to label an image based on the frequent patterns of its low-level visual features. According to the specialty of image segmentation, effectivealgorithms are implemented to mine such patterns and to generate labeling rules. It is shown in the experiments on authoritative and real datasets that our method is more effective than some previously proposed methods for labeling images containing multiple concepts.
%K Content-based image retrieval
%K Semantic concepts
%K Frequent patterns
%K Multiple concept labeling<br>基于内容的图像检索
%K 语义概念
%K 频繁模式
%K 多概念标注
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=0F1609E4D36E41F9352CBA71046969D8&yid=A732AF04DDA03BB3&vid=339D79302DF62549&iid=38B194292C032A66&sid=C5F8B8CB20F1B3D8&eid=DABEF202280E7EF1&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=15