A Modified Fuzzy ART for Image Segmentation

Authors:
A. Gumina
Affiliations:
-
Venue:
ICIAP '01 Proceedings of the 11th International Conference on Image Analysis and Processing
Year:
2001

Citing 0
Cited 2

Fusion of GRNN and FA for Online Noisy Data Regression

Neural Processing Letters
Multiscale cancer modeling: In the line of fast simulation and chemotherapy

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Abstract: This paper presents a clustering approach for image segmentation based on a modified fuzzy ART model. The goal of the proposed approach is to find a simple model able to instance a prototype for each cluster in order to avoid complex post-processing phases. Some results and comparisons with other models present in literature, like SOM and original fuzzy ART have been presented. Qualitative and quantitative evaluations confirm the validity of our approach.