DocumentCode
1645615
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
fYear
2001
Firstpage
102
Lastpage
107
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Processing, 2001. Proceedings. 11th International Conference on
Conference_Location
Palermo
Print_ISBN
0-7695-1183-X
Type
conf
DOI
10.1109/ICIAP.2001.956992
Filename
956992
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