Abstract
Principle Component Analysis (PCA) technique is of vital importance and is an efficient method in extracting features in face recognition. Generally speaking, the image always needs to be transformed into ID vector in PCA. Recently two-dimensional PCA (2DPCA) technique has been proposed. In the method of 2DPCA, PCA technique is applied directly on the original images without being transformed into 1D vector. In this paper, we will compare the two methods in face recognition based on ORL face database.
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© 2011 Springer-Verlag Berlin Heidelberg
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Haiyang, Z. (2011). A Comparison of PCA and 2DPCA in Face Recognition. In: Wan, X. (eds) Electrical Power Systems and Computers. Lecture Notes in Electrical Engineering, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21747-0_55
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DOI: https://doi.org/10.1007/978-3-642-21747-0_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21746-3
Online ISBN: 978-3-642-21747-0
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