Dzung Dinh Nguyen

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In this paper, intuitionistic interval type-2 fuzzy c-means clustering (InIT2FCM) method is proposed for the clustering problems. Intuitionistic fuzzy sets (IFS) and intuitionistic type-2 fuzzy sets (InIT2FS) were introduced with the aim to better handle the uncertainty. Utilizing the advantages of the IFS and InT2FS, we have combined them with fuzzy(More)
In this paper, an image thresholding method based on Intuitionistic Type-2 Fuzzy Sets (InT2FS) method is introduced for the segmentation problems. Besides, intuitionistic type-2 fuzzy set has been formed as an extension of intuitionistic fuzzy set for handling uncertainty. As we know, the image data which usually contains noises or uncertainty so then(More)
This paper presents a novel approach for visual fire detection by modelling the spatial structure of fire, this structure is considered in terms of the color intensity of fire-color pixels. To model this structure, the authors uses an interval type-2 fuzzy clustering algorithm with some modification to separate fire-color pixels into some clusters, then(More)
In this paper, kernel interval type-2 fuzzy c-means clustering (KIT2FCM) and multiple kernel interval type 2 fuzzy c-means clustering (MKIT2FCM) are proposed as a base for classification problems. Besides building algorithms KIT2FCM to overcome some drawback of the conventional FCM and use the advantages of fuzzy clustering technique on the interval type 2(More)