Pose Invariant Face Recognition Using DT-CWT Partitioning and KPCA

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K. Punnam Chandar
K. Punnam Chandar
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T. Satyasavithri
T. Satyasavithri
α Kakatiya University

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Pose Invariant Face Recognition Using DT-CWT Partitioning and KPCA

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Abstract

In this paper the suitability of Dual Tree Complex Wavelet Transform for pose invariant Face Recognition is studied and a feature extraction frame work is proposed. This proposed framework will aid in design of Face Recognition system to address the challenging issue like Pose Variation. In contrast to the discrete wavelet Transform (DWT) the design of Dual Tree Complex Wavelet Transform is rugged to shift Invariance and poses good directional properties. These features of DT-CWT motivated to study their suitability for Face Feature Extraction, as the features of face are oriented in different directions. In this proposed frame work the Image is decomposed using DT-CWT and the features are extracted from low frequency band using Kernel Principal Component analysis (KPCA). To show the performance, the proposed method is tested on ORL Database. Satisfactory results are obtained using proposed method compared to existing state of art.

References

15 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

K. Punnam Chandar. 2014. \u201cPose Invariant Face Recognition Using DT-CWT Partitioning and KPCA\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 14 (GJCST Volume 14 Issue F5): .

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Issue Cover
GJCST Volume 14 Issue F5
Pg. 15- 20
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Version of record

v1.2

Issue date

December 31, 2014

Language
en
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In this paper the suitability of Dual Tree Complex Wavelet Transform for pose invariant Face Recognition is studied and a feature extraction frame work is proposed. This proposed framework will aid in design of Face Recognition system to address the challenging issue like Pose Variation. In contrast to the discrete wavelet Transform (DWT) the design of Dual Tree Complex Wavelet Transform is rugged to shift Invariance and poses good directional properties. These features of DT-CWT motivated to study their suitability for Face Feature Extraction, as the features of face are oriented in different directions. In this proposed frame work the Image is decomposed using DT-CWT and the features are extracted from low frequency band using Kernel Principal Component analysis (KPCA). To show the performance, the proposed method is tested on ORL Database. Satisfactory results are obtained using proposed method compared to existing state of art.

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Pose Invariant Face Recognition Using DT-CWT Partitioning and KPCA

K. Punnam Chandar
K. Punnam Chandar Kakatiya University
T. Satyasavithri
T. Satyasavithri

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