martes, 26 de septiembre de 2017

Ficha del recurso:

Fuente:

Vínculo original en 2011 INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENTAL SCIENCE-ICEES 2011, 11 10.1016/j.egypro.2011.10.296 2011
Jiang, YX; Ren, B

Última actualización:

jueves, 12 de abril de 2012

Entrada en el observatorio:

jueves, 12 de abril de 2012

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Local gabor characteristic integrated with LDP for face recognition with one training sample

Traditional methods get low recognition accuracy in the condition of only one training sample. A new face recognition method based on local Gabor phase characteristic and locality dispersing projection (LGP/LDP) is proposed. In our proposed method, according to the good spatial position and orientation of Gabor filter, a Gabor filter with four frequencies and six orientations is firstly applied to filter face images. Based on Daugman's method and the local Exclusive- or (XOR) pattern, local Gabor patterns are then extracted to form the characteristic images. Finally, LDP is used to project the characteristic images of each spatial position and orientation into low dimensional space. Neighbor classifier is adopted and the classified information is fused to get the recognition result. Experimental results show that our method consistently outperforms other recognition method based on Principal Component Analysis (PCA), LDP and local Gabor phase characteristic integrated with P! CA (LGP/PCA). (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Organizers of 2011 International Conference on Energy and Environmental Science.