Title :
A modified fuzzy ART for image segmentation
Author :
Cinque, L. ; Foresti, G.L. ; Gumina, A. ; Levialdi, S.
Author_Institution :
Dipartimento di Sci. dell´´Inf., Rome Univ., Italy
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 the literature, like SOM and original fuzzy ART are presented. Qualitative and quantitative evaluations confirm the validity of our approach
Keywords :
ART neural nets; fuzzy neural nets; image segmentation; pattern clustering; clustering approach; image segmentation; modified fuzzy ART model; Clustering algorithms; Computational complexity; Computer architecture; Image edge detection; Image segmentation; Neural networks; Prototypes; Remuneration; Subspace constraints; Testing;
Conference_Titel :
Image Analysis and Processing, 2001. Proceedings. 11th International Conference on
Conference_Location :
Palermo
Print_ISBN :
0-7695-1183-X
DOI :
10.1109/ICIAP.2001.956992
