NDLI: Face recognition by fast independent component analysis and genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Yi-qiong Xu Bi-cheng Li Bo Wang
Copyright Year	2004
Description	Author affiliation: Dept. of Inf. Sci., Inf. Eng. Univ., Zhengzhou, China (Yi-qiong Xu; Bi-cheng Li; Bo Wang)
Abstract	In this paper, ICA is presented as an efficient feature extraction algorithm used in automatic face recognition task. In a task such as face recognition, important information may be contained in the high-order relationship among pixels. ICA is sensitive to high-order statistic in the data and finds not-necessarily orthogonal bases, so it may better identify and reconstruct high-dimensional face image data. ICA algorithms are time-consuming and sometimes converge difficultly. So a modified FastICA algorithm is developed in this paper, which only need to computer Jacobian matrix once time in one iteration and achieves the correspondent effect of Fast-ICA. After obtaining all independent components, a genetic algorithm is introduced to select optimal independent components (ICs). In this paper, ICA is compared with principle component analysis (PCA) based feature extraction method. The experiment results show that modified FastICA algorithm fast convergence speed and genetic algorithm optimize recognition performance. ICA based features extraction method is robust to variations and promising for face recognition.
Sponsorship	Wuhan Univ. Univ. of Aizu, Japan Nat. Natural Sci. Found. China IEEE Eng. in Medicine and Biology Soc
Starting Page	194
Ending Page	198
File Size	238453
Page Count	5
File Format	PDF
ISBN	0769522165
DOI	10.1109/CIT.2004.1357196
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Jacobian matrices Image converters Face recognition Independent component analysis Feature extraction Statistics Image reconstruction Genetic algorithms Principal component analysis Convergence
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

Fast Independent Component Analysis Based Digital Modulation Recognition Method

Illumination Variation in Images in Independent Component Analysis and Principal Component Analysis Subspaces

Feature extraction using evolutionary weighted principal component analysis

Radar Target Recognition Using A Modified FastICA Algorithm plus GAs

Genetic algorithm applied to ICA feature selection

Face Recognition Using Improved Fast PCA Algorithm

Optimizing modular image PCA using Genetic algorithm for expression - Invariant face recognition

Face recognition using feature extraction based on independent component analysis

Face recognition based on fuzzy Independent Component Analysis

Face recognition by fast independent component analysis and genetic algorithm

Similar Documents

Fast Independent Component Analysis Based Digital Modulation Recognition Method

Illumination Variation in Images in Independent Component Analysis and Principal Component Analysis Subspaces

Feature extraction using evolutionary weighted principal component analysis

Radar Target Recognition Using A Modified FastICA Algorithm plus GAs

Genetic algorithm applied to ICA feature selection

Face Recognition Using Improved Fast PCA Algorithm

Optimizing modular image PCA using Genetic algorithm for expression - Invariant face recognition

Face recognition using feature extraction based on independent component analysis

Face recognition based on fuzzy Independent Component Analysis

Face recognition by fast independent component analysis and genetic algorithm