An effective model for Heterogeneous Face recognition in a static background

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ANUPAMA; Dr.Madhu.H.Gowda; Dr.Mamatha.C.M

An effective model for Heterogeneous Face recognition in a static background

Authors: ANUPAMA, Dr.Madhu.H.Gowda, Dr.Mamatha.C.M

Unique Paper ID: 153486
Volume: 8
Issue: 7
PageNo: 372-376

Keywords: Adaboost DoG Face Recognition Heterogeneous MB-LBP

Abstract:
Real time faces images are captured in different spectral bands are referred to as heterogeneous. In this paper, the new approach based on low resolution heterogeneous face recognition and synthesis is proposed. In the recognition section, multi block local binary pattern (MBLBP) is used as facial representation for low resolution images. Then Canonical Correlation Analysis (CCA) is a applied to learn the mapping between the different LBP-face patterns. The corresponding matching scores are calculated in the CCA subspace for the final decision. In the synthesis section, according to the CCA transformation matrices obtained above, we apply ridge regression to determine an approximate linear relation between the target pattern image and the projection vector of the probe. The work shows a practical solution for reliable heterogeneous face synthesis.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 7
PageNo: 372-376

An effective model for Heterogeneous Face recognition in a static background

Available:https://ijirt.org/article?manuscript=153486

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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