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- Title
隶属度修正的空间核直觉模糊聚类 苗族服饰图案分割.
- Authors
彭家磊; 黄成泉; 覃小素; 雷欢; 陈阳; 周丽华
- Abstract
Aiming at the problem that the intuitionistic fuzzy clustering algorithm does not consider the spatial neighborhood information, a spatial kernel intuitionistic fuzzy clustering algorithm for Miao costume patterns segmentation with modified membership was proposed. First, the membership constraint penalty term was added to the objective function of the intuitionistic fuzzy C-means (IFCM) algorithm to reduce the computational complexity of the algorithm. Second, the kernel distance was utilized as the proposed algorithm instead of the Euclidean distance to recalculate the distances from pixel points to cluster centers, which can obtain high robustness. Finally, the spatial neighborhood information was considered, different weights were assigned to the pixel points in the neighborhood to modify the membership function, and thus the final image segmentation results were achieved. The experimental results show that in the noisy Miao costume patterns dataset, the partition coefficient and partition entropy of the proposed algorithm are 95. 49% and 7.44%. In the colorful Miao costume patterns dataset, the partition coefficient and partition entropy of the proposed algorithm are 97.91% and 3. 42%, which are better than other comparison algorithms, and the operation efficiency of the kernel function is improved.
- Subjects
FUZZY algorithms; EUCLIDEAN algorithm; IMAGE segmentation; COMPUTATIONAL complexity; MEMBERSHIP functions (Fuzzy logic); EUCLIDEAN distance; KERNEL functions
- Publication
Wool Textile Journal, 2023, Vol 51, Issue 9, p117
- ISSN
1003-1456
- Publication type
Article
- DOI
10.19333/j.mfkj.20230103109