Comparative Study of PCA and LDA

Chetana Narkhede, Uma Nagaraj

Abstract: Face recognition gains a lot of courtesy in recent years due to its various applications in our societies. In the appearance-based face recognition classical principal component analysis (PCA) and linear component analysis (LDA) algorithms are widely used. Small database marks the robust result of these algorithms principally. These algorithms are mainly used for feature point extraction and dimensionality reduction in 2D face recognition. We present a comparison of both the algorithms and combination of these two algorithms.

Keywords: Principle component analysis, linear discriminant analysis, face recognition, dimensionality reduction, Eigenfaces

How to Cite?: Chetana Narkhede, Uma Nagaraj, "Comparative Study of PCA and LDA", Volume 4 Issue 4, April 2015, International Journal of Science and Research (IJSR), Pages: 1107-1110, https://www.ijsr.net/getabstract.php?paperid=SUB152772, DOI: https://dx.doi.org/10.21275/SUB152772

Download Citation: APA | MLA | BibTeX | EndNote | RefMan