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Reseach Article

A Novel NSCT based Illuminant Invariant Extraction with Optimized Edge Detection Technique for Face Recognition

by S. H. Krishna Veni, K. L. Shunmuganathan, L. Padma Suresh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 3
Year of Publication: 2013
Authors: S. H. Krishna Veni, K. L. Shunmuganathan, L. Padma Suresh
10.5120/11940-7733

S. H. Krishna Veni, K. L. Shunmuganathan, L. Padma Suresh . A Novel NSCT based Illuminant Invariant Extraction with Optimized Edge Detection Technique for Face Recognition. International Journal of Computer Applications. 70, 3 ( May 2013), 7-10. DOI=10.5120/11940-7733

@article{ 10.5120/11940-7733,
author = { S. H. Krishna Veni, K. L. Shunmuganathan, L. Padma Suresh },
title = { A Novel NSCT based Illuminant Invariant Extraction with Optimized Edge Detection Technique for Face Recognition },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 3 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number3/11940-7733/ },
doi = { 10.5120/11940-7733 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:31:52.120191+05:30
%A S. H. Krishna Veni
%A K. L. Shunmuganathan
%A L. Padma Suresh
%T A Novel NSCT based Illuminant Invariant Extraction with Optimized Edge Detection Technique for Face Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 3
%P 7-10
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel integrated approach for resolving the effect of illumination changes on face recognition is proposed. This face recognition system comprises feature extraction, feature selection and recognition. For feature extraction, a normal shrink filter in NSCT domain denoising technique is applied which produces illuminant invariant for the given image. In the second phase, to capture the important geometrical structures and to reduce the feature dimensionality Ant colony Optimization algorithm is performed. This combined approach fairly detects the edges with improved quality. Finally for recognition, a graph matching algorithm is employed. This algorithm utilizes a group of feature points to explore their geometrical relationship in a graph arrangement. While applying the entire method to the yaleB database, experimental results shows that the proposed work yields the best subset of features and provides a better solution for complex illumination problems.

References
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Index Terms

Computer Science
Information Sciences

Keywords

illuminant invariant Non subsampled contourlet feature subset Ant colony optimization Weighted graph matching