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A Neutrosophic Approach Based on TOPSIS Method to Image Segmentation
Author(s) -
Guojing Xu,
Shiyu Wang,
Tian Yang,
Wen Jiang
Publication year - 2018
Publication title -
international journal of computers communications and control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.422
H-Index - 33
eISSN - 1841-9844
pISSN - 1841-9836
DOI - 10.15837/ijccc.2018.6.3268
Subject(s) - computer science , topsis , segmentation , artificial intelligence , image (mathematics) , image segmentation , fuzzy logic , domain (mathematical analysis) , pattern recognition (psychology) , graphics , data mining , computer vision , mathematics , operations research , mathematical analysis , computer graphics (images)
Neutrosophic set (NS) is a formal framework proposed recently. NS can not only describe the incomplete information in the decision-making system but also depict the uncertainty and inconsistency, so it has applied successfully in several fields such as risk assessment, fuzzy decision and image segmentation. In this paper, a new neutrosophic approach based on TOPSIS method, which can make full use of NS information, is proposed to separate the graphics. Firstly, the image is transformed into the NS domain. Then, two operations, a modified alpha-mean and the beta-enhancement operations are used to enhance image edges and to reduce uncertainty. At last, the segmentation is achieved by the TOPSIS method and the modified fuzzy c-means (FCM). Simulated images and real images are illustrated that the proposed method is more effective and accurate in image segmentation.

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