Local Color Vector Binary Patterns From Multichannel Face Images for Face Recognition

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This paper proposes a novel face descriptor based on color information, i.e., so-called local color vector binary patterns (LCVBPs), for face recognition (FR). The proposed LCVBP consists of two discriminative patterns: color norm patterns and color angular patterns. In particular, we have designed a method for extracting color angular patterns, which enables to encode the discriminating texture patterns derived from spatial interactions among different spectral-band images. In order to perform FR tasks, the proposed LCVBP feature is generated by combining multiple features extracted from both color norm patterns and color angular patterns. Extensive and comparative experiments have been conducted to evaluate the proposed LCVBP feature on five public databases. Experimental results show that the proposed LCVBP feature is able to yield excellent FR performance for challenging face images. In addition, the effectiveness of the proposed LCVBP feature has successfully been tested by comparing other state-of-the-art face descriptors.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2012-04
Language
English
Article Type
Article
Keywords

CLASSIFICATION; NORMALIZATION

Citation

IEEE TRANSACTIONS ON IMAGE PROCESSING, v.21, no.4, pp.2347 - 2353

ISSN
1057-7149
DOI
10.1109/TIP.2011.2181526
URI
http://hdl.handle.net/10203/101117
Appears in Collection
EE-Journal Papers(저널논문)
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