Face recognition for different facial exprisions based on pca, lda analysis
International Journal of Development Research
Face recognition for different facial exprisions based on pca, lda analysis
Received 07th April, 2017; Received in revised form 29th May, 2017; Accepted 26th June, 2017; Published online 31st July, 2017
Copyright ©2017, Chandolu Prasanthi and Jayesh Gangrade. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The face is our primary focus of attention in social intercourse, playing a major role in identity. We can recognize thousands of faces in our lifetime and identify familiar faces at glance even after years of separation but it is difficult for computer compared with the human brain. In this paper presents comparative study of PCA (Principal Components Analysis) and LDA (Linear Discriminant Analysis) which are most popular appearance-based approaches in face recognition. PCA is recognized as an optimal method to perform dimension reduction. LDA once proposed to obtain better classification by using class information. Disputes over the comparison of PCA and LDA have motivated to study their performance. The Database of Faces which comprises 40 subjects with 10 images each, both recognition results have revealed the superiority of LDA over PCA for this medium-sized database.
