Using discriminant eigenfeatures for image retrieval
Using discriminant eigenfeatures for image retrieval
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DOI：
10.1109/34.531802
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发表时间：
1996-08-01
影响因子：
23.6
通讯作者：
Weng, JJ
中科院分区：
文献类型：
--
作者：
Swets, DL;Weng, JJ
本文描述了利用多维判别分析和相关的最优线性投影理论从图像训练集中自动选择特征的方法。我们展示了这些最具区别性的特征对基于视图的类检索的有效性，这些类检索来自一个大型数据库，该数据库包含广泛变化的现实世界对象，呈现为“框架良好”的视图，并将其与主成分分析的效果进行了比较。
This paper describes the automatic selection of features from an image training set using the theories of multidimensional discriminant analysis and the associated optimal linear projection. We demonstrate the effectiveness of these Most Discriminating Features for view-based class retrieval from a large database of widely varying real-world objects presented as ''well-framed'' views, and compare it with that of the principal component analysis.