A High Precision Feature Based on LBP and Gabor Theory for Face Recognition

Sensors

Wei Xia²  Shouyi Yin¹ 

[1]Tsinghua Center for Mobile Computing, Institute of Microelectronics, Tsinghua University, Beijing 100084, China

关键词: face recognition;    new feature;    robust;    Gabor;    LBP;    PCA;    LDA;   

DOI  :  10.3390/s130404499

来源: mdpi

【 摘 要 】

How to describe an image accurately with the most useful information but at the same time the least useless information is a basic problem in the recognition field. In this paper, a novel and high precision feature called BG2D2LRP is proposed, accompanied with a corresponding face recognition system. The feature contains both static texture differences and dynamic contour trends. It is based on Gabor and LBP theory, operated by various kinds of transformations such as block, second derivative, direct orientation, layer and finally fusion in a particular way. Seven well-known face databases such as FRGC, AR, FERET and so on are used to evaluate the veracity and robustness of the proposed feature. A maximum improvement of 29.41% is achieved comparing with other methods. Besides, the ROC curve provides a satisfactory figure. Those experimental results strongly demonstrate the feasibility and superiority of the new feature and method.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.