A face - recognition algorithm based on fisher linear discriminant analysis is studied in detail which combines principal component analysis ( pca ) based eigenface method and linear discriminant analysis ( lda ) method 該方法將基于主成分分析( pca )的特征臉方法和基于線性判別分析( lda )的分類方法有機的結(jié)合起來。
The basic mission of feature extraction is to identify a set of features that are most effective for subsequent classification task from a set of candidate features . the state of the art in feature extraction methods includes statistics - based methods ( e . g 現(xiàn)有的特征提取方法主要有基于統(tǒng)計的特征提取(主分量分析( pca )和fisher線性判別分析( flda )是兩種最常用的方法) 、基于知識的特征提取及基于神經(jīng)網(wǎng)絡的特征提取等。
To retrieval directly information with images , by using the face detection technique based on the gravity - center template matching method and the face recognition technique based on methods of the principal component analysis and the linear discriminative analysis 摘要為了能直接通過圖像檢索自己所需要的信息,提出了一種直接根據(jù)人臉圖像來檢索信息的技術(shù),采用基于重心模板匹配的人臉檢測技術(shù)與主成分分析方法、線性判別分析方法相結(jié)合的人臉識別技術(shù)設計并實現(xiàn)了一個人臉圖像檢索系統(tǒng)。