Hybrid Segmentation Method for Grayscale Images

Hybrid Segmentation Method for Grayscale Images

In this paper, we propose a hybrid segmentation method based on the fuzzy clustering approach and mathematical morphology. First, the grayscale image is segmented using a Fast and Robust Fuzzy C-means algorithm that takes into account the spatial information. Then, the clustering result is refined u...

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Bibliographic Details
Published in:2018 IEEE 5th International Congress on Information Science and Technology (CiSt) pp. 290 - 295
Main Authors: Barrah, Hanane, Cherkaoui, Abdeljabbar
Format: Conference Proceeding
Language:English
Published: IEEE 01-10-2018
Subjects:
C-means algorithm
Clustering algorithms
Fuzzy clustering
Gray-scale
Image segmentation
Linear programming
Morphology
Partitioning algorithms
Robustness
Spatial information
Online Access:Get full text
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Summary:In this paper, we propose a hybrid segmentation method based on the fuzzy clustering approach and mathematical morphology. First, the grayscale image is segmented using a Fast and Robust Fuzzy C-means algorithm that takes into account the spatial information. Then, the clustering result is refined using some morphological operations. The fastness and the robustness of the proposed method are demonstrated on a synthetic and some real images, where valuable results were obtained.
ISSN:2327-1884
DOI:10.1109/CIST.2018.8596675