NDLI: Enhanced face recognition through variation of Principle Component Analysis (PCA)

Content Provider	IEEE Xplore Digital Library
Author	Meedeniya, D.A. Ratnaweera, D.A.A.C.
Copyright Year	2007
Description	Author affiliation: Dept. of Stat. & Comput. Sci., Univ. of Peradeniya, Peradeniya (Meedeniya, D.A.)
Abstract	Face recognition, the art of matching a given face to a database of faces, is a non-intrusive biometric method that dates back to the 1960s. Facial recognition systems are built on computer programs that analyze images of human faces for the purpose of identifying them. The paper presents a new method for face recognition. This can cope with different lightning conditions and different distorted levels in facial images. This method relies on a variation of Principal Component Analysis (PCA) technique. The algorithm extracts the eigan values and eigan vectors from the images. It performs the economic size singular value decomposition to obtain a unitary matrix, which is use for recognition. The images are recognized base on the minimum distance. The system finds the closest match from the database to the incoming image. The system uses the ldquoOlivetti face databaserdquo as the face image database. The database contains 10 images of each person in the group. The proposed system will take a picture that is not included in the database and match it to a picture of the same person that is within the image database. Experimental results demonstrate that the proposed approach can efficiently recognize human faces. This system satisfactorily deals with the problems caused by using other face recognition systems. This algorithm can achieve 93.7% and higher performance. Successful results were obtained in different situations where images have taken under different lighting conditions. The proposed method reduces the computational load. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power.
Starting Page	347
Ending Page	352
File Size	621921
Page Count	6
File Format	PDF
ISBN	9781424411511
DOI	10.1109/ICIINFS.2007.4579200
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-09
Publisher Place	Sri Lanka
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Biometrics Art Image analysis Image databases Face recognition Humans Lightning Power generation economics Principal component analysis Singular value decomposition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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