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A Novel Iris Recognition Based on PSO-RBFNN

机译:基于PSO-RBFNN的新型虹膜识别

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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.
机译:在本文中,提出了一种自适应的虹膜边界检测方法,并且该方法可以准确地将虹膜区域分段,而不管虹膜边界的形状。同时,基于使用特殊Gabor滤波器的组合的新特征提取技术提出了小波最大组件。最后,提出了具有粒子群优化(PSO)的径向基函数神经网络(RBFNN)具有智能分类器的新型虹膜IRIS识别技术,用于高性能虹膜识别,本文结合了径向基函数神经网络(RBFNN)和粒子群优化(PSO)用于优化的PNN分类器模型。实验结果揭示了所提出的算法在虹膜识别方面提供卓越的性能。

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