A NEW PICTURE FUZZY CLUSTERING METHOD TO SEGMENT  THE SURFACE WATER FROM SATELLITE IMAGES

Phạm Huy Thông; Phùng Thế Huân; Hoàng Thị Cành; Trần Thị Ngân

doi:10.34238/tnu-jst.6342

A NEW PICTURE FUZZY CLUSTERING METHOD TO SEGMENT THE SURFACE WATER FROM SATELLITE IMAGES

About this article

Received: 09/08/22 Revised: 07/10/22 Published: 07/10/22

Authors

1. Pham Huy Thong, 1) Graduate School of Science and Technology, Vietnam Academy of Science and Technology 2) Insitute of Information Technology, Vietnam Academy of Science and Technology 3) VNU Information Technology Institute
2. Phung The Huan , TNU - University of Information and Communication Technology
3. Hoang Thi Canh, TNU - University of Information and Communication Technology
4. Tran Thi Ngan, Thuyloi University

Abstract

In recent years, the research directions on advanced fuzzy sets have been received a lot of attention from scientists, typically studies on Picture Fuzzy Set (PFS).Picture fuzzy set was proposed to solve the problems of noisy data in order to improve the clustering performance. With four membership degrees, including the positive, the neutral, the negative and the refusal, the optimal models using Picture fuzzy set have more choices and may yield more accurate results. In this paper, we propose a new Picture fuzzy clustering method named as PFSFCM. The proposedmethod is implemented and experimentally compared against the related methods, including the standard Picture fuzzy clustering (FCPFS), and the Confidence-weighted safe semi-supervised clustering (CS3FCM)inquality of clustering results with both of UCI dataset and Seattle Surface Water Dataset. The experimental results show that theproposed method has better performance comparing to selected methods on the same datasets.

Keywords

Clustering; Fuzzy clustering; Picture fuzzy set; Satellite image; Surface water

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DOI: https://doi.org/10.34238/tnu-jst.6342

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