Rate the Article: Improvement in Recognition Rate by Using Linear Regression with Principal Component Analysis, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 109 | Views: 348

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014 | Rating: 6.7 / 10


Improvement in Recognition Rate by Using Linear Regression with Principal Component Analysis

Tanvi Ahuja, Vinit Agarwal


Abstract: In this paper we propose a face recognition system which use the combination of Regression and PCA (Principal Component Analysis). We use regression for classification of eigen vectors generated and PCA for extraction of facial features. The results obtained are more accurate than the previous approaches.


Keywords: Face Recognition, Eigen Vectors, PCA, Linear Regression, Euclidean Distance


Edition: Volume 3 Issue 11, November 2014,


Pages: 647 - 650



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