Research Article | OPEN ACCESS
Performance Evaluation of LDA, CCA and AAM
1M. Jasmine Pemeena Priyadarsini, 2K. Murugesan, 1Srinivasa Rao Inbathini, 1J. Vishal, 1S. Anand and 1Rahul N. Nair
1School of Electronics Engineering, VIT University, India
2Sree Sastha Institute of Engineering and Technology, Chennai, India
Research Journal of Applied Sciences, Engineering and Technology 2015 9:685-699
Received: July 18, 2014 | Accepted: October 17, 2014 | Published: March 25, 2015
Abstract
Wouldn't we love to replace passwords access control to avoid theft, forgotten passwords? Wouldn't we like to enter the security areas just in seconds? Yes the answer is face recognition. In this study we explore and compare the performance of three algorithms namely LDA, CCA, AAM. LDA (an evolution of PCA is a dimensionality reduction technique where it solves the problem of illumination to some extent, maximizing the inter class separation and minimizing the intra class variations. CCA, a measure of linear relationship between two multidimensional variables where it takes the advantage of PCA and LDA for maximizing the correlation and better performance. AAM is a model based approach where it just picks the landmarks of the images for recognition therefore reducing the error rate and producing good performance rate.
Keywords:
AAM, CCA, efficiency , face recognition , landmarks , LDA , PCA, performance,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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