NDLI: Face Recognition Based on Wavelet Transform Weighted Modular PCA

Content Provider	IEEE Xplore Digital Library
Author	Zhao, Minghua Li, Peng Liu, Zhifang
Copyright Year	2008
Abstract	A new algorithm named wavelet transform weighted modular PCA is proposed for face recognition. Firstly, the training images and the testing image are preprocessed with wavelet transform and the LL band and the LH/HL average band are divided into sub-images with the same size. Secondly, the prospective classify contribution of each sub-model of the two bands are computed. Thirdly, each sub-image of the two bands of the testing image is projected to its corresponding subspace and the confidence values with each image are obtained. Finally, the two confidence values with each image are added with a weight and the total confidence value is obtained to classify the testing image. Experimental results show that the recognition rate of the proposed algorithm is about 4%-6% superior to traditional methods.
Starting Page	589
Ending Page	593
File Size	548593
Page Count	5
File Format	PDF
ISBN	9780769531199
DOI	10.1109/CISP.2008.138
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-05-27
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Face recognition wavelet transform Data mining Computer science Signal processing algorithms Computer graphics Signal processing face recognition wavelet transform weighted modular PCA projection Probes Principal component analysis Testing
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

Face recognition based on PCA on wavelet subband

Research of face recognition based on wavelet transform and principal component analysis

Face Recognition using Multiresolution PCA

Face Recognition Based on Wavelet Transform and PCA

Hybrid parallel approach based on wavelet transformation and principle component analysis for solving face recognition problem

A Highly-Efficient Face Recognition Method Based on Weighted LDA

Study and analysis of face recognition system using Principal Component Analysis (PCA)

Efficiency Improvement for Unconstrained Face Recognition by Weightening Probability Values of Modular PCA and Wavelet PCA

Development of algorithms for face and character recognition based on wavelet transforms, PCA and neural networks

Face Recognition Based on Wavelet Transform Weighted Modular PCA

Similar Documents

Face recognition based on PCA on wavelet subband

Research of face recognition based on wavelet transform and principal component analysis

Face Recognition using Multiresolution PCA

Face Recognition Based on Wavelet Transform and PCA

Hybrid parallel approach based on wavelet transformation and principle component analysis for solving face recognition problem

A Highly-Efficient Face Recognition Method Based on Weighted LDA

Study and analysis of face recognition system using Principal Component Analysis (PCA)

Efficiency Improvement for Unconstrained Face Recognition by Weightening Probability Values of Modular PCA and Wavelet PCA

Development of algorithms for face and character recognition based on wavelet transforms, PCA and neural networks

Face Recognition Based on Wavelet Transform Weighted Modular PCA