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Radiographic Image Segmentation Based on Gaussian Mixture Model

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Radiographic Image Segmentation Based on Gaussian Mixture Model

F. Mekhalfa, N. Nacereddine and A. B. Goumeïdane

Welding and NDT Research Center Cheraga, Algeria

faizamek@yahoo.fr

Abstract — In this work, we propose to use an image segmentation method based on Gaussian mixture model. The observed image is considered as a mixture of multivariate densities and the mixture parameters are estimated by the expectation maximization (EM) algorithm. The segmentation is completed by clustering each pixel into a component according to the maximum likelihood (ML) estimation.

This method has been applied to a variety of radiographic images of weld defects and satisfactory segmentation results have been reported.

Key Words: — expectation maximization algorithm, fuzzy C-means algorithm, Gaussian mixture model, image segmentation, radiographic images, Weld defect.

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