文章基本信息

标题：KEYWORD AND IMAGE CONTENT FEATURES FOR IMAGE INDEXING AND RETRIEVAL WITHIN COMPRESSED DOMAIN
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作者：Irianto . ; Y. Suhendro
期刊名称：Jurnal Informatika
印刷版ISSN：1411-0105
出版年度：2009
卷号：10
期号：2
页码：73-78
DOI：10.9744/informatika.10.2.73-78
语种：English
出版社：Institute of Research and Community Outreach - Petra Christian University
摘要：The central problem of most Content Based Image Retrieval approaches is poor quality in terms of sensitivity (recall) and specificity (precision). To overcome this problem, the semantic gap between high-level concepts and low-level features has been acknowledged. In this paper we introduce an approach to reduce the impact of the semantic gap by integrating high-level (semantic) and low-level features to improve the quality of Image Retrieval queries. Our experiments have been carried out by applying two hierarchical procedures. The first approach is called keyword-content, and the second content-keyword. Our proposed approaches show better results compared to a single method (keyword or content based) in term of recall and precision. The average precision has increased by up to 50%.
关键词：CBIR, high level, low level features, recall, precision.