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2014 | OriginalPaper | Chapter

Disguised Face Recognition Based on Local Feature Fusion and Biomimetic Pattern Recognition

Authors : Ying Xu, Yikui Zhai, Junying Gan, Junying Zeng

Published in: Biometric Recognition

Publisher: Springer International Publishing

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Disguised face recognition (FR) is considered as one of the difficult and important problems in FR field. Rather than disguised modeling, a disguised face recognition algorithm based on local feature fusion and geometry coverage is presented in this paper. Local binary pattern (LBP) and local phase quantization (LPQ) is firstly applied to extract the binary and phase statistics features which are robust to the disguised mode, then hyper sausage neuron based on biomimetic pattern recognition (BPR) theory is adopted to construct high-dimensional geometry coverage of different classes, which makes full use of continuous characteristics of identical class face features while avoids the interruption of the disguised mode. Experiments on AR face database and disguised face database established by police face combination software show that, compared with the state-of-the-art methods, the proposed recognition algorithm can achieve high recognition results under disguised conditions.

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Metadata
Title
Disguised Face Recognition Based on Local Feature Fusion and Biomimetic Pattern Recognition
Authors
Ying Xu
Yikui Zhai
Junying Gan
Junying Zeng
Copyright Year
2014
Publisher
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-12484-1_10

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