基于模糊熵的空间语义图像检索模型研究  

Research of spatial semantic image retrieval model based on fuzzy entropy

作　　者：蒋华伟[1] 

机构地区：[1]河南工业大学信息科学与工程学院,郑州450001

出　　处：《计算机应用研究》2010年第1期353-357,共5页Application Research of Computers

基　　金：河南省教育厅自然科学研究基金资助项目(2008A520005);博士基金资助项目(2006BS007)

摘　　要：根据模糊熵理论和改进的空间信息分布,提出了颜色空间特征语义图像检索模型。阐述基于语法规则的颜色空间特征语义描述方法,构造从低层颜色空间特征到高层语义之间的映射,根据这些模糊语义值进行图像检索。实验结果表明,该模型能够有效地对图像高层语义进行刻画,由此实现的模型不仅能获得高效和稳定的检索结果,获得与人类视觉感知较好的一致性,该算法还能很好地消除低层图像空间特征和高层语义之间的语义鸿沟。According to the theory of fuzzy entropy and the improved spatial information distribution, the paper put forward the novel model of color spatial features semantic retrieval. Set the color spatial semantic features description method forth based on grammar rule,constructed the mapping from low-level color spatial features to high-level semantic features successfully, and proposed the fuzzy retrieval algorithm according to the extracted semantic features. The experimental results show that the mod- el is effective in characterizing image high-level semantic content, the approach not only has an excellent retrieval precision and a good accordance with human visual percetion, but also has strong significance for reducing the semantic gap between the image spatial features and semantic features.

关 键 词：模糊信息熵 基于内容的图像检索 空间特征语义 语言变量 

分 类 号：TP392[自动化与计算机技术—计算机应用技术] TP311.52[自动化与计算机技术—计算机科学与技术]