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

    Fatma Mallouli

    Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 243-248, 2019, DOI:10.31209/2019.100000069

    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-IrisTwins. The obtained results have shown More >

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