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一种新的图像语义与视觉特征的映射方法
引用本文:杨珺,王继成,邢丹俊. 一种新的图像语义与视觉特征的映射方法[J]. 计算机应用, 2008, 28(10): 2558-2560
作者姓名:杨珺  王继成  邢丹俊
作者单位:同济大学,电子与信息工程学院,上海,201804;上海电力学院,计算机与信息工程学院,上海,200090;同济大学,电子与信息工程学院,上海,201804
摘    要:建立低层视觉特征与高层语义的映射关系能够很好地解决图像检索中的“语义鸿沟”问题。提出一种图像视觉特征与高层语义的映射方法。该方法通过用户的相关反馈来获得图像的语义信息,构造图像特征-语义决策表并结合粗糙集中的知识约简删除了与语义无关的冗余特征,实现了高层语义与底层视觉特征的映射。实验结果表明该方法能够显著减少与语义无关的视觉特征数量,降低分类的复杂性和计算代价,具有较好的分类准确率。

关 键 词:图像检索  特征提取  粗糙集  相关反馈
收稿时间:2008-04-25

A novel mapping method for image semantics and visual features
YANG Jun,WANG Ji-cheng,XING Dan-jun. A novel mapping method for image semantics and visual features[J]. Journal of Computer Applications, 2008, 28(10): 2558-2560
Authors:YANG Jun  WANG Ji-cheng  XING Dan-jun
Affiliation:YANG Jun1,2,WANG Ji-cheng1,XING Dan-jun1(1. School of Electronics , Information Engineering,Tongji University,Shanghai 201804,China,2. School of Computer , Information Engineering,Shanghai University of Power,Shanghai 200090,China)
Abstract:Establishing a mapping relationship between image visual features and semantics can be used to reduce semantic gap. A novel mapping method for image semantics and visual features was presented. In this method, image semantic information could be captured by adding users' relevance feedback, and then a decision table of visual features and semantics was constructed. Knowledge reduction of rough set theory was used to reduce the redundant visual features according to semantics, by doing that a mapping relatio...
Keywords:image retrieval  feature extraction  rough sets  relevance feedback
本文献已被 CNKI 维普 万方数据 等数据库收录!
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