INTUITIONISTIC ROBUST CLUSTERING FOR SEGMENTATION OF LESIONS IN DERMATOSCOPIC IMAGES

CELIA RAMOS PALENCIA; DANTE MUJICA VARGAS; JEAN MARIE VIANNEY KINANI KINANI; ANTONIO LUNA ALVAREZ; NOE ALEJANDRO CASTRO SANCHEZ

doi:https://doi.org/10.6036/10787

PAPER SENDING SUBSCRIPTION

Search engine :

DYNA JOURNAL ENGINEERING

Skip to the menu
Skip to the content

Return to the menu

Search

Vote:

Results:

0 points

0 Votes

INTUITIONISTIC ROBUST CLUSTERING FOR SEGMENTATION OF LESIONS IN DERMATOSCOPIC IMAGES

JANUARY 2024 - Volume: 99 - Pages: 44-51

DOI:

https://doi.org/10.6036/10787

Authors:

CELIA RAMOS PALENCIA

DANTE MUJICA VARGAS

- JEAN MARIE VIANNEY KINANI KINANI -

ANTONIO LUNA ALVAREZ

NOE ALEJANDRO CASTRO SANCHEZ

Disciplines:

Computer Sciences (ARTIFICIAL INTELLIGENCE / INTELIGENCIA ARTIFICIAL )

Downloads: 48

How to cite this paper:

Download pdf

Download pdf

Received Date : 13 December 2022

Reviewing Date : 15 December 2022

Accepted Date : 29 March 2023

Key words:: Agrupamiento Difuso Intuitivo Robusto, Imágenes Dermatoscópicas, Delimitación de Lesiones, Estimador M-Redescendente, Robust Intuitionistic Fuzzy Clustering, Dermoscopic Images, Delimitations of Lesions, M-redescending Estimator, M-redescending, robust, fuzzy, clustering, dermoscopic
Article type:: ARTICULO DE INVESTIGACION / RESEARCH ARTICLE
Section:: RESEARCH ARTICLES

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

Share: