DocumentCode
2832058
Title
High performance iris recognition based on LDA and LPCC
Author
Chu, Chia Te ; Chen, Ching-Han
Author_Institution
Inst. of Electr. Eng., I-Shou Univ., Kaohsiung
fYear
2005
fDate
16-16 Nov. 2005
Lastpage
421
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
Keywords
biometrics (access control); eye; image recognition; neural nets; particle swarm optimisation; high performance iris recognition; particle swarm optimization; probabilistic neural network; Discrete wavelet transforms; Feature extraction; Histograms; Image databases; Iris recognition; Linear discriminant analysis; Neural networks; Particle swarm optimization; Tellurium; Wavelet transforms; iris recognition; particle swarm optimization; probabilistic neural network; wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1082-3409
Print_ISBN
0-7695-2488-5
Type
conf
DOI
10.1109/ICTAI.2005.71
Filename
1562972
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