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
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
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), https://www.ijsr.net/search_index_results_paperid.php?id=OCT14894, Volume 3 Issue 11, November 2014, 647 - 650
51 PDF Views | 26 PDF Downloads
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