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- W2392934552 abstract "Two-way compression project subspace method combining both the Two-dimension Principle Component Analysis(2DPCA) and the Two-dimension Linear Discriminant Analysis(2DLDA) was proposed for face recognition.This method first transposes the feature matrix after it performs the 2DPCA and then it performs the 2DLDA.Compared with the(2D)2PCA and(2D)2LDA,this method makes full use of the advantages of the 2DPCA and 2DLDA.It not only contains the sample category information,but also eliminates the image matrix correlation of the row and co-lumn,so that it effectively extracts the row and column recognition information,and meanwhile,the recognition feature dimension decreases dramatically.The experiment on the ORL and PERET face databases shows that the recognition rate of this method is better than the existing two-dimension feature extract method without influencing the recognition speed." @default.
- W2392934552 created "2016-06-24" @default.
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- W2392934552 date "2009-01-01" @default.
- W2392934552 modified "2023-09-22" @default.
- W2392934552 title "New Method of Tow Direction and Two Dimension Extract Features for Face Recognition" @default.
- W2392934552 hasPublicationYear "2009" @default.
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