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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