1 July 2011 Infrared face recognition based on intensity of local micropattern-weighted local binary pattern
Zhihua Xie, Guodong Liu
Author Affiliations +
Funded by: National Nature Science Foundation of China
Abstract
The traditional local binary pattern (LBP) histogram representation extracts the local micropatterns and assigns the same weight to all local micropatterns. To combine the different contributions of local micropatterns to face recognition, this paper proposes a weighted LBP histogram based on Weber's law. First, inspired by psychological Weber's law, intensity of local micropattern is defined by the ratio between two terms: one is relative intensity differences of a central pixel against its neighbors and the other is intensity of local central pixel. Second, regarding the intensity of local micropattern as its weight, the weighted LBP histogram is constructed with the defined weight. Finally, to make full use of the space location information and lessen the complexity of recognition, the partitioning and locality preserving projection are applied to get final features. The proposed method is tested on our infrared face databases and yields the recognition rate of 99.2% for same-session situation and 96.4% for elapsed-time situation compared to the 97.6 and 92.1% produced by the method based on traditional LBP.
©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Zhihua Xie and Guodong Liu "Infrared face recognition based on intensity of local micropattern-weighted local binary pattern," Optical Engineering 50(7), 077201 (1 July 2011). https://doi.org/10.1117/1.3594788
Published: 1 July 2011
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Infrared radiation

Facial recognition systems

Infrared imaging

Binary data

Feature extraction

Thermography

Databases

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