Comparitive Study on Face Recognition Using HGPP, PCA, LDA, ICA and SVM

Comparitive Study on Face Recognition Using HGPP, PCA, LDA, ICA and SVM

Article ID

CSTGVJZ559

Comparitive Study on Face Recognition Using HGPP, PCA, LDA, ICA and SVM

Dr. Hardik Kadiya GTU

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Abstract

We are comparing the performance of five algorithms of the face recognition i.e. HGPP, PCA, LDA, ICA and SVM. The basis of the comparison is the rate of accuracy of face recognition. These algorithms are employed on the ATT database and IFD database. We find that HGPP has the highest rate of accuracy of recognition when it is applied on the ATT database whereas LDA outperforms the all other algorithms when it is applied to IFD database.

Comparitive Study on Face Recognition Using HGPP, PCA, LDA, ICA and SVM

Authors

Dr. Hardik Kadiya GTU

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How to Cite

Dr. Hardik Kadiya. 2013. “. Global Journal of Computer Science and Technology – F: Graphics & Vision GJCST-F Volume 12 (GJCST Volume 12 Issue F15): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

GJCST Volume 12 Issue F15
Pg. 55- 58

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Submission Received February 10, 2012
Accepted March 5, 2012
Published March 15, 2012

Keywords

Face recognition HGPP ICA LDA PCA SVM

Article Matrices

Total Score: 106

Country: India

Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision

Authors: Dr. Hardik Kadiya (PhD/Dr. count: 1)

View Count (all-time): 204

Total Views (Real + Logic): 9860

Total Downloads (simulated): 2516

Publish Date: 2013 01, Sat

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Total Views: 9860

Total Downloads: 2516

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