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Soft Computing

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01.02.2015 | Methodologies and Application

An iterative fuzzy region competition algorithm for multiphase image segmentation

verfasst von: V. R. Borges, D. Guliato, C. A. Z. Barcelos, M. A. Batista

Erschienen in: Soft Computing | Ausgabe 2/2015

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Abstract

This paper presents a new multiphase image segmentation model based on Fuzzy Region Competition. The proposed model approximates image regions by probability density functions and uses a supervised approach in the segmentation process. The strategy of the proposed model is to perform a two-phase Fuzzy Region Competition model iteratively for image segmentation. The hard partition is obtained in each step from a determined fuzzy membership functions consequently, the segmentation process is soft, while the final result is hard, due to the simplicity of avoiding non-overlapping and vacuum regions. Finally, several experiments on multiphase images are presented to demonstrate the efficiency and robustness of the proposed model when dealing with noisy, texturized and natural images.

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Titel: An iterative fuzzy region competition algorithm for multiphase image segmentation
verfasst von: V. R. Borges
D. Guliato
C. A. Z. Barcelos
M. A. Batista
Publikationsdatum: 01.02.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 2/2015
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-014-1256-2

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