International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Since Year 2012 | Open Access | Double Blind Reviewed

ISSN: 2319-7064


Downloads: 109

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 11, November 2014


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

Tanvi Ahuja | Vinit Agarwal [3]


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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How to Cite this Article?

Tanvi Ahuja, Vinit Agarwal, "Improvement in Recognition Rate by Using Linear Regression with Principal Component Analysis", International Journal of Science and Research (IJSR), Volume 3 Issue 11, November 2014, pp. 647-650, https://www.ijsr.net/get_abstract.php?paper_id=OCT14894

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