High performance iris recognition based on LDA and LPCC

Chia-te Chu, Ching-Han Chen
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引用次数: 51

Abstract

In this paper, the iris recognition algorithm based on LPCC and LDA is first presented. So far, the two algorithms are not found for iris recognition in literature. In addition, a simple and fast training algorithm, particle swarm optimization (PSO), is also introduced for training the probabilistic neural network (PNN). Finally, a comparative experiment of existing methods for iris recognition is evaluated on CASIA iris image databases. The proposed algorithms can achieve 100% recognition rates and the result is encouraging
基于LDA和LPCC的高性能虹膜识别
本文首先提出了一种基于LPCC和LDA的虹膜识别算法。到目前为止,文献中还没有发现这两种算法用于虹膜识别。此外,还介绍了一种简单快速的训练算法——粒子群优化算法(PSO),用于训练概率神经网络。最后,在CASIA虹膜图像数据库上对现有的虹膜识别方法进行了对比实验。所提出的算法可以达到100%的识别率,结果令人鼓舞
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