Computer Science ›› 2015, Vol. 42 ›› Issue (7): 305-308.doi: 10.11896/j.issn.1002-137X.2015.07.065

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Soft Combination of Probabilistic Neural Network Classifiers for Face Recognition

ZHAI Jun-hai ZHAO Wen-xiu   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Probabilistic neural network (PNN) classifiers have fast learning speed and can be easily implemented.The outputs of PNN are posterior probabilities which facilitate the soft combination of classifiers.We proposed a face recognition algorithm named SCPNN,which combines PNN classifiers with fuzzy integral,and makes full use of the superiori-ty of PNN and ensemble learning.The main steps of the proposed method include:the incomplete wavelet packet decomposition of face images,training PNN classifiers with wavelet subspace images which include low frequency components and combination of the trained PNN classifiers by fuzzy integral.The proposed algorithm SCPNN was compared with 3 matrix subspace algorithms on 4 face databases,which are JAFFE,YALE,ORL and FERET.The experimental results confirm that the proposed method outperforms the 3 matrix subspace algorithms in recognition accuracy and CPU time.

Key words: Probabilistic neural networks,Face recognition,Fuzzy integral,Wavelet transform,Subspace

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