NDLI: Multi scale feature extraction and enhancement using SVD towards secure Face Recognition system

Content Provider	IEEE Xplore Digital Library
Author	Chandar, K.P. Chandra, M.M. Kumar, M.R. Latha, B.S.
Copyright Year	2011
Description	Author affiliation: Department Of EEE, Kakatiya Institute of Technology and Science (KITS), Warangal-15, INDIA (Latha, B.S.) \|\| Dept. Of ECE, University College of Engineering (KU), Warangal-15, INDIA (Chandar, K.P.) \|\| Kakatiya Institute of Technology and Science (KITS), Warangal-15, INDIA (Chandra, M.M.; Kumar, M.R.)
Abstract	Biometric devices provide secure mechanism towards gaining access. One of the Biometric features is Face and the system implemented is Face Recognition system. The Classical Face Recognition System is implemented with Principal Component Analysis and is successful. PCA is a linear method of extracting the features in a lower dimension space and is severely affected by the Pose and surrounding illumination variation. To implement effective face recognition system, pose variation is to be considered and the problem is well addressed with Kernel PCA (nonlinear PCA). KPCA extracts features in a higher dimension space, there by the system is rugged to pose variation. The illumination variation is accounted for capture range of the front end device and its surrounding and is not dealt in KPCA. In this work Singular Value Decomposition is used to deal with surrounding illumination and wavelets are employed to aid the KPCA in capturing the Multi Scale Features there by making the System robust to pose and illumination variation. To show the performance, the proposed method is tested on YaleB, ORL Databases. The results obtained show the impact of the method and is compared with PCA, KPCA.
Starting Page	64
Ending Page	69
File Size	1823270
Page Count	6
File Format	PDF
ISBN	9781612846545
e-ISBN	9781612846538
DOI	10.1109/ICSCCN.2011.6024516
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-21
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	SVD Databases Face recognition Lighting Feature extraction KPCA and Euclidean Classifier Face Kernel Discrete Wavelet Transform Principal component analysis PCA
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Preprocessing using SVD towards illumination invariant face recognition

Suitability of Complex Wavelets towards Face Recognition

Facial Recognition Based on Kernel PCA

Face recognition using wavelet transform and Kernel Principal Component Analysis

Feature extraction using PCA and Kernel-PCA for face recognition

Face Recognition Based on Wavelet Transform and PCA

Multiple resolution based palm print recognition using 2D-DWT and Kernel PCA

An Efficient Face Recognition System Using DWT-ICA Features

Rescaling of low frequency DCT coefficients with Kernel PCA for illumination invariant face recognition

Multi scale feature extraction and enhancement using SVD towards secure Face Recognition system

Similar Documents

Preprocessing using SVD towards illumination invariant face recognition

Suitability of Complex Wavelets towards Face Recognition

Facial Recognition Based on Kernel PCA

Face recognition using wavelet transform and Kernel Principal Component Analysis

Feature extraction using PCA and Kernel-PCA for face recognition

Face Recognition Based on Wavelet Transform and PCA

Multiple resolution based palm print recognition using 2D-DWT and Kernel PCA

An Efficient Face Recognition System Using DWT-ICA Features

Rescaling of low frequency DCT coefficients with Kernel PCA for illumination invariant face recognition

Multi scale feature extraction and enhancement using SVD towards secure Face Recognition system