PSO-RBFNN Based Optimized PNN Classifier Model

被引:0
|
作者
Liu, Jin [1 ]
Fu, Xiao [1 ]
Yao, Xingbin
机构
[1] Air Force Aviat Univ, Dept Fundamental Courses, Changchun, Peoples R China
关键词
iris recognition; Probabilistic neural network; Particle swarm optimization; RBF neural networks;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, a self-adaptive method of iris boundary detection is presented and the method can segment the iris area accurately regardless of the shapes of iris boundaries. On the same time, a new feature extraction technique based on combination using special Gabor filters and wavelet maxima components is proposed. Finally, The radial basis function neural network (RBFNN) with a particle swarm optimization (PSO) a novel iris iris recognition technique with intelligent classifier is proposed for high performance iris recognition. this paper combines radial basis function neural network (RBFNN) and particle swarm optimization (PSO) for an optimized PNN classifier model. The experimental results reveal the proposed algorithm provides superior performance in iris recognition.
引用
收藏
页码:456 / 459
页数:4
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