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Face Recognition: A Literature Review

Nawaf Hazim Barnouti, Sinan Sameer Mahmood Al-Dabbagh, Wael Esam Matti. Published in Image Processing

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Nawaf Hazim Barnouti, Sinan Sameer Mahmood Al-Dabbagh, Wael Esam Matti
10.5120/ijais2016451597
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  1. Nawaf Hazim Barnouti, Sinan Sameer Mahmood Al-dabbagh and Wael Esam Matti. Face Recognition: A Literature Review. International Journal of Applied Information Systems 11(4):21-31, September 2016. URL, DOI BibTeX

    @article{10.5120/ijais2016451597,
    	author = "Nawaf Hazim Barnouti and Sinan Sameer Mahmood Al-dabbagh and Wael Esam Matti",
    	title = "Face Recognition: A Literature Review",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "September 2016",
    	volume = 11,
    	number = 4,
    	month = "Sep",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "21-31",
    	numpages = 11,
    	url = "http://www.ijais.org/archives/volume11/number4/934-2016451597",
    	doi = "10.5120/ijais2016451597",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

Face recognition have gained a great deal of popularity because of the wide range of applications such as in entertainment, smart cards, information security, law enforcement, and surveillance. It is a relevant subject in pattern recognition, computer vision, and image processing. Two major methods are used for features extraction, which can be classified into appearance-based and Model-based methods. Appearance-based methods use global representations to identify a face. Model-based face methods aim to construct a model of the human face that capture facial variations. Image similarity is the distance between the vectors of two images. This paper contains Four sections. The first section discusses face recognition applications with examples. The second section discuss the common feature face recognition methods. The third section discuss distance measurement classifiers. The fourth section discuss different face recognition databases.

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Keywords

PCA, LDA, ICA, KPCA, KLDA, EBGM