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首页> 外文会议>Conference on multimedia storage and archiving systems >Content-based image retrieval via adaptive multifeature templates
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Content-based image retrieval via adaptive multifeature templates

机译：通过自适应多功能模板进行基于内容的图像检索

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Abstract: The use of image content analysis and image clustering techniques to organize an image database with a great variety of collections is investigated in this work. The objective is to bridge the gap between low-level features and their high level semantic meanings. We attempt this goal by using both coarse and fine classifications in image database organization. Image content analysis serves as the major tool in coarse classification. A set of typical image collections are studied by training their low-level feature vectors. Clusters of representative low-level features are further provided in form of semantic templates to provide fine-level classification clues for achieving a good query performance and serving as a supporting tool for browsing. With these multiple feature semantic templates, an interactive retrieval process can be conveniently implemented to incorporate user's feedback to achieve the desired query. !13
机译：摘要：在这项工作中，研究了使用图像内容分析和图像聚类技术来组织具有各种各样集合的图像数据库。目的是弥合低级功能与其高级语义之间的差距。我们通过在图像数据库组织中同时使用粗分类和细分类来尝试实现此目标。图像内容分析是粗分类的主要工具。通过训练它们的低级特征向量来研究一组典型的图像集合。进一步以语义模板的形式提供了代表性的低级特征的集群，以提供用于实现良好查询性能并用作浏览支持工具的高级分类线索。使用这些多特征语义模板，可以方便地实现交互式检索过程，以合并用户的反馈以实现所需的查询。 ！13

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