A novel hybrid approach based on sub-pattern technique and whitened PCA for face recognition

NCUIR > Engineering College > Graduate Institute of Mechanical Engineering > journal & Dissertation > Item 987654321/26826

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/26826

Title:	A novel hybrid approach based on sub-pattern technique and whitened PCA for face recognition
Authors:	Hsieh,PC;Tung,PC
Contributors:	機械工程研究所
Keywords:	COMPONENT ANALYSIS
Date:	2009
Issue Date:	2010-06-29 18:01:09 (UTC+8)
Publisher:	中央大學
Abstract:	Recently, in a task of face recognition, some researchers presented that independent component analysis (ICA) Architecture I involves a vertically centered principal component analysis (PCA) process (PCA 1) and ICA Architecture II involves a whitened horizontally centered PCA process (PCA II). They also concluded that the performance of ICA strongly depends on its involved PCA process. This means that the computationally expensive ICA projection is unnecessary for further process and involved PCA process of ICA, whether PCA I or II, can be used directly for face recognition. But these approaches only consider the global information of face images. Some local information may be ignored. Therefore, in this paper, the sub-pattern technique was combined with PCA I and PCA II, respectively, for face recognition. In other words, two new different sub-pattern based whitened PCA approaches (which are called Sp-PCA I and Sp-PCA II, respectively) were performed and compared with PCA I, PCA II, PCA, and sub-pattern based PCA (SpPCA). Then, we find that sub-pattern technique is useful to PCA I but not to PCA II and PCA. Simultaneously, we also discussed what causes this result in this paper. At last, by simultaneously considering global and local information of face images. we developed a novel hybrid approach which combines PCA II and Sp-PCA I for face recognition. The experimental results reveal that the proposed novel hybrid approach has better recognition performance than that obtained using other traditional methods. (C) 2008 Elsevier Ltd. All rights reserved.
Relation:	PATTERN RECOGNITION
Appears in Collections:	[Graduate Institute of Mechanical Engineering] journal & Dissertation

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