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

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

Dr. Hardik Kadiya

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α Gujarat Technological University

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

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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.

References

19 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Hardik Kadiya. 2013. \u201cComparitive Study on Face Recognition Using HGPP, PCA, LDA, ICA and SVM\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 12 (GJCST Volume 12 Issue F15): .

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GJCST Volume 12 Issue F15
Pg. 55- 58

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Face recognition HGPP ICA LDA PCA SVM

Submission ReceivedFebruary 10, 2012
Peer Review Double Blind
Handling Editor
Accepted March 5, 2012
Published March 15, 2012

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v1.2

Issue date

January 5, 2013

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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): 246

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Publish Date: 2013 01, Sat

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Total Views: 9929

Total Downloads: 2616

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