Intuitionistic Robust Clustering for Segmentation of Lesions in Dermatoscopic Images
Auteur(s): |
Celia Ramos Palencia
Dante Mujica Vargas Antonio Luna Alvarez Noe Alejandro Castro Sanchez |
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Médium: | article de revue |
Langue(s): | espagnol |
Publié dans: | DYNA, 1 janvier 2024, n. 1, v. 99 |
Page(s): | 44-51 |
DOI: | 10.6036/10787 |
Abstrait: |
This paper presents the formulation of the intuitive fuzzy clustering algorithm to be robust to atypical data present in dermoscopic images and to delimit the affected area. This algorithm is formulated from the objective function derivation for memberships update, to integrate an m-redescending estimator influence function. Experimentation shows an accuracy of 95% with the proposal algorithm with respect to other clustering algorithms to perform delimitations, in addition the iterations number is considerably reduced. Keywords: Robust Intuitionistic Fuzzy Clustering, Dermoscopic Images, Delimitations of Lesions, M-redescending Estimator |
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sur cette fiche - Reference-ID
10756366 - Publié(e) le:
14.01.2024 - Modifié(e) le:
14.01.2024