Abstract
This paper presents a robust segmentation method based on the integrated squared error or L 2 estimation (L 2 E). Formulated under the Finite Gaussian Mixture (FGM) framework, the new model (FGML2E) has a strong discriminative ability in capturing the major parts of intensity distribution without being affected by outlier structures or heavy noise. Comparisons are made with two popular solutions, the EM and FCM algorithms, and the experimental results clearly show the improvement made by our model.
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Xie, S., Liu, J., Berryman, D., List, E., Smith, C., Chebrolu, H. (2007). A Robust Image Segmentation Model Based on Integrated Square Estimation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_63
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DOI: https://doi.org/10.1007/978-3-540-76856-2_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76855-5
Online ISBN: 978-3-540-76856-2
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