Face Recognition Based on Eigenface Image Reconstruction and Fisherface

Abstract:

In this paper, a new face recognition method based on eigenface image reconstruction and Fisherface is proposed, it is mainly used to reduce the loss of personal characteristics. First, we can obtain the feature subspace of all the classes in training set by using the inner-classes covariance matrix as generating matrix, and so we get the eigenfaces of each person (class). Next, we use the principal component of testing set, which is obtained by mapping testing set to the feature subspace, to reconstruct the testing images. Finally, we substitute the reconstructed testing images for the original ones, and then get the recognition work completed by using Fisherface method. The simulation illustrates the effectivity of the method on the ORL face database.

• Periodical: Advanced Materials Research (Volumes 1044-1045)
• Pages: 1153-1158
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1044-1045.1153
• Online since: October 2014
• Authors: Xiao Long Lu, Le Yang, Gang Cai, Zi Xing Mo, Li Peng*
• Keywords: Eigenface, Face Recognition, Fisherface, Image Reconstruction, PCA

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