An effective model for Heterogeneous Face recognition in a static background

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

An effective model for Heterogeneous Face recognition in a static background
Author(s):
ANUPAMA, Dr.Madhu.H.Gowda, Dr.Mamatha.C.M
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.
Article Details
Unique Paper ID: 153486 Publication Volume & Issue: Volume 8, Issue 7 Page(s): 372 - 376
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