文章基本信息

标题：Content Based Image Retrieval System Consume Semantic Gap
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作者：K. Vijay Kumar ; Dr.R.Rajeswara Rao ; V.Subba Ramaiah 等
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2012
卷号：3
期号：5
页码：5231-5235
出版社：TechScience Publications
摘要：In order to improve the retrieval accuracy of contentbased image retrieval systems, research focus has been shifted from designing sophisticated low-level feature extraction algorithms to reducing the ‘semantic gap’ between the visual features and the richness of human semantics. This paper attempts to provide a comprehensive survey of the recent technical achievements in high-level semantic-based image retrieval. Major recent publications are included in this survey covering different aspects of the research in this area, including low-level image feature extraction,similarity measurement, and deriving high-level semantic features. We identify five major categories of the state-of-the-art techniques in narrowing down the ‘semantic gap’: (1) using object ontology to define high-level concepts; (2) using machine learning methods to associate lowlevel features with query concepts; In addition, some other related issues such as image test bed and retrieval performance evaluation are also discussed. Finally, based on existing technology and the demand from real-world applications, a few promising future research directions are suggested.
关键词：Content-based image retrieval; Semantic gap;Image;segmentation; Gabor Filters