Ear recognition based on feature fusion and Bagging neural network
基于多特征融合和Bagging神经网络的人耳识别

A new ear recognition method based on feature fusion was presented. Firstly, ear projection coefficient features were extracted by NMF methods. Then these features were combined with the ear rotation invariance Zemike moments features so as to get a new feature which had higher discriminating power. With this new feature, a Bagging neural network was built up by using bagging algorithm that improved classification accuracy and generalization of neural network. At last, the results of some comparative experiments show that this ear recognition method can get higher recognitiori rate.