scholarly journals Approach to image segmentation based on interval neutrosophic set

2020 ◽  
Vol 10 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Ye Yuan ◽  
◽  
Yan Ren ◽  
Xiaodong Liu ◽  
Jing Wang ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Neutrosophic Set ◽  
Interval Neutrosophic Set

scholarly journals A NOVEL IMAGE SEGMENTATION APPROACH BASED ON NEUTROSOPHIC SET AND IMPROVED FUZZY C-MEANS ALGORITHM

2011 ◽  
Vol 07 (01) ◽  
pp. 155-171 ◽  
Author(s):  
H. D. CHENG ◽  
YANHUI GUO ◽  
YINGTAO ZHANG
Keyword(s):  
Image Segmentation ◽  
Point Of View ◽  
Neutrosophic Set ◽  
Convergence Criterion ◽  
Complex Objects ◽  
Fuzzy C Means ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Segmentation Approach ◽  
Fuzzy C Means Algorithm

Image segmentation is an important component in image processing, pattern recognition and computer vision. Many segmentation algorithms have been proposed. However, segmentation methods for both noisy and noise-free images have not been studied in much detail. Neutrosophic set (NS), a part of neutrosophy theory, studies the origin, nature, and scope of neutralities, as well as their interaction with different ideational spectra. However, neutrosophic set needs to be specified and clarified from a technical point of view for a given application or field to demonstrate its usefulness. In this paper, we apply neutrosophic set and define some operations. Neutrosphic set is integrated with an improved fuzzy c-means method and employed for image segmentation. A new operation, α-mean operation, is proposed to reduce the set indeterminacy. An improved fuzzy c-means (IFCM) is proposed based on neutrosophic set. The computation of membership and the convergence criterion of clustering are redefined accordingly. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can segment images accurately and effectively. Especially, it can segment the clean images and the images having different gray levels and complex objects, which is the most difficult task for image segmentation.

scholarly journals An Adaptive Region Growing Based on Neutrosophic Set in Ultrasound Domain for Image Segmentation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 60584-60593 ◽  
Author(s):  
Xue Jiang ◽  
Yanhui Guo ◽  
Haibin Chen ◽  
Yaqin Zhang ◽  
Yao Lu
Keyword(s):  
Image Segmentation ◽  
Region Growing ◽  
Neutrosophic Set

Time-aware trustworthiness ranking prediction for cloud services using interval neutrosophic set and ELECTRE

2017 ◽  
Vol 138 ◽  
pp. 27-45 ◽  
Author(s):  
Hua Ma ◽  
Haibin Zhu ◽  
Zhigang Hu ◽  
Keqin Li ◽  
Wensheng Tang
Keyword(s):  
Cloud Services ◽  
Neutrosophic Set ◽  
Interval Neutrosophic Set ◽  
Time Aware

scholarly journals NC-TODIM Based MAGDM under Neutrosophic Cubic Set Environment

2017 ◽  
Author(s):  
Surapati Pramanik ◽  
Shyamal Dalapati ◽  
Shariful Alam ◽  
Tapan Kumar Roy
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Attenuation Factor ◽  
Neutrosophic Set ◽  
Conduct Sensitivity Analysis ◽  
Todim Method ◽  
Interval Neutrosophic Set ◽  
Ranking Order ◽  
The Impact

Neutrosophic cubic set is the hybridization of the concept of neutrosophic set and interval neutrosophic set. Neutrosophic cubic set has the capacity to express the hybrid information of both the interval neutrosophic set and the single valued neutrosophic set simultaneously. As newly defined, little research on the operations and applications of neutrosophic cubic sets appear in the current literature. In the present paper we propose the score, accuracy functions for neutrosophic cubic sets and prove their basic properties. We firstly develop TODIM method to solve multi attribute group decision making in neutrosophic cubic set environment, which we call NC-TODIM. Also, we solve a MAGDM problem using the proposed NC-TODIM method to show the applicability and effectiveness of the developed method. We also conduct sensitivity analysis to show the impact of ranking order of the alternatives for different values of attenuation factor of losses for multi-attribute group decision making problem.

scholarly journals New Similarity and Entropy Measures of Interval Neutrosophic Sets with Applications in Multi-Attribute Decision-Making

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 370 ◽  
Author(s):  
Han Yang ◽  
Xiaoman Wang ◽  
Keyun Qin
Keyword(s):  
Decision Making ◽  
Hamming Distance ◽  
Similarity Measures ◽  
Neutrosophic Set ◽  
Inclusion Relation ◽  
Neutrosophic Sets ◽  
Information Measures ◽  
Interval Neutrosophic Set ◽  
Multi Attribute Decision Making ◽  
Interval Neutrosophic Sets

Information measures play an important role in the interval neutrosophic sets (INS) theory. The main purpose of this paper is to study the similarity and entropy of INS and its application in multi-attribute decision-making. We propose a new inclusion relation between interval neutrosophic sets where the importance of the three membership functions may be different. Then, we propose the axiomatic definitions of the similarity measure and entropy of the interval neutrosophic set (INS) based on the new inclusion relation. Based on the Hamming distance, cosine function and cotangent function, some new similarity measures and entropies of INS are constructed. Finally, based on the new similarity and entropy, we propose a multi-attribute decision-making method and illustrate that these new similarities and entropies are reasonable and effective.

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