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Research Paper | Computer Science Engineering | Volume 3 Issue 11, November 2014 | Pages: 647 - 650 | India
Improvement in Recognition Rate by Using Linear Regression with Principal Component Analysis
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
How to Cite?: Tanvi Ahuja, Vinit Agarwal, "Improvement in Recognition Rate by Using Linear Regression with Principal Component Analysis", Volume 3 Issue 11, November 2014, International Journal of Science and Research (IJSR), Pages: 647-650, https://www.ijsr.net/getabstract.php?paperid=OCT14894, DOI: https://dx.doi.org/10.21275/OCT14894