DocumentCode :
2314213
Title :
Automatic extraction of linguistic models for image description
Author :
Baturone, Illuminada ; Gersnoviez, Andrés
Author_Institution :
Microelectron. Inst. of Seville, Univ. of Seville, Seville, Spain
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
This paper describes a methodology to extract fuzzy models that describe linguistically the low-level features of an image (such as color, texture, etc.). The methodology combines grid-based algorithms with clustering and tabular simplification methods to compress image information into a small number of fuzzy rules with high linguistic meaning. All the steps of the methodology are carried out with the help offered by the tools of Xfuzzy 3 environment, so we can define, simplify, tune and verify the fuzzy models automatically. Several examples are included to illustrate the advantages of the methodology.
Keywords :
computational linguistics; feature extraction; fuzzy logic; grid computing; image coding; image recognition; pattern clustering; clustering methods; feature extraction; fuzzy models; fuzzy rules; grid-based algorithms; image description; image information compression; linguistic models; tabular simplification methods; Argon;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5584798
Filename :
5584798
Link To Document :
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