DocumentCode :
2227173
Title :
PZM/ANN hybrid network for face recognition
Author :
Sun, JinGuang ; Yang, Di ; Qin, HongWei
Author_Institution :
Comput. Sci. & Technol. Dept., Liaoning Tech. Univ., LNTU, Huludao, China
Volume :
4
fYear :
2010
fDate :
20-22 Aug. 2010
Abstract :
Improved Pseudo-Zernike Moment (PZM) and artificial neural network (ANN) was combined within the hybrid architecture for face recognition. Improved PZM was used to extract face feature, and encoded to form the input vector sending to ANN. Experimental results demonstrate the present approach taking advantage of ANN, basically eliminates the effects of the change of face scale and rotation, and has better robust to variation of illumination, pose and facial expression. On the basis of previous study, the approach makes a further discussion on the application of Pseudo-Zernike Moments in the aspect of face recognition.
Keywords :
face recognition; feature extraction; neural nets; artificial neural network; face recognition; facial expression; feature extraction; hybrid network; pose expression; pseudo zernike moment; Analytical models; Computational modeling; Databases; Optical imaging; artificial neural network; component; face recognition; improved pseudo-Zernike moment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
ISSN :
2154-7491
Print_ISBN :
978-1-4244-6539-2
Type :
conf
DOI :
10.1109/ICACTE.2010.5579494
Filename :
5579494
Link To Document :
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