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Robust EM Algorithm for Iris Segmentation based on Mixture of Gaussian Distribution


Authors



Abstract

Density estimation via Gaussian mixture modelling has been successfully applied to image segmentation. In this paper, we have learned distributions mixture model to the pixel of an iris image as training data. We introduce the proposed algorithm by adapting the Expectation-Maximization (EM) algorithm. To further improve the accuracy for iris segmentation, we consider the EM algorithm in Markovian and non Markovian cases. Simulated data proves the accuracy of our algorithm. The proposed method is tested on a subset of the CASIA database by Chinese Academy of Sciences Institute of Automation-Iris-Twins. The obtained results have shown a significant improvement of our approach compared to the standard version of EM algorithm and the classical segmentation method.


Keywords


Pages

Total Pages: 6
Pages: 243-248

DOI
10.31209/2019.100000069


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Published

Volume: 25
Issue: 2
Year: 2019

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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