DocumentCode :
598069
Title :
Local Line Derivative Pattern for face recognition
Author :
Zhichao Lian ; Meng Joo Er ; Yang Cong
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
fYear :
2012
fDate :
Sept. 30 2012-Oct. 3 2012
Firstpage :
1449
Lastpage :
1452
Abstract :
In this paper, we propose a novel face descriptor for face recognition, named Local Line Derivative Pattern (LLDP). High-order derivative images in two directions are obtained by convolving original images with Sobel Masks. A revised binary coding function is proposed and three standards on arranging the weights are also proposed. Based on the standards, the weights of a line neighborhood in two directions are arranged. The LLDP labels in two directions are calculated with the proposed binary coding function and weights. The labeled image is divided into blocks where spatial histograms are extracted separately and concatenated into an entire histogram as features for recognition. The experiments on the FERET and Extended Yale B show superior performances of the proposed LLDP compared to other existing methods based on the LBP. The results prove that the LLDP has good robustness against expression, illumination and aging variations.
Keywords :
binary codes; face recognition; feature extraction; image coding; Extended Yale B database; FERET database; LLDP labels; Sobel masks; aging variation robustness; binary coding function; expression variation robustness; face descriptor; face recognition; high-order derivative images; illumination variation robustness; labeled image division; line neighborhood weights; local line derivative pattern; spatial histogram concatenation; spatial histogram extraction; Aging; Face; Face recognition; Histograms; Lighting; Robustness; Standards; Face recognition; High-order local pattern; Local binary pattern;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1522-4880
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2012.6467143
Filename :
6467143
Link To Document :
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