Efficient decomposition methods of fuzzy relation and their application to image decomposition

Hajime Nobuhara; Kaoru Hirota; Salvatore Sessa; Witold Pedrycz

doi:10.1016/j.asoc.2004.09.002

Efficient decomposition methods of fuzzy relation and their application to image decomposition

Hajime Nobuhara^*, Kaoru Hirota, Salvatore Sessa, Witold Pedrycz

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

20 Citations (Scopus)

Abstract

Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.

Original language	English
Pages (from-to)	399-408
Number of pages	10
Journal	Applied Soft Computing
Volume	5
Issue number	4
DOIs	https://doi.org/10.1016/j.asoc.2004.09.002
Publication status	Published - Jul 2005
Externally published	Yes

Keywords

Fuzzy relation
Gradient method
Image decomposition
Optimization

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10.1016/j.asoc.2004.09.002

Cite this

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title = "Efficient decomposition methods of fuzzy relation and their application to image decomposition",

abstract = "Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.",

keywords = "Fuzzy relation, Gradient method, Image decomposition, Optimization",

author = "Hajime Nobuhara and Kaoru Hirota and Salvatore Sessa and Witold Pedrycz",

year = "2005",

month = jul,

doi = "10.1016/j.asoc.2004.09.002",

language = "English",

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journal = "Applied Soft Computing",

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T1 - Efficient decomposition methods of fuzzy relation and their application to image decomposition

AU - Nobuhara, Hajime

AU - Hirota, Kaoru

AU - Sessa, Salvatore

AU - Pedrycz, Witold

PY - 2005/7

Y1 - 2005/7

N2 - Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.

AB - Two optimizations for decomposition problem of fuzzy relation (image) are proposed. The first optimization is a fast decomposition method of fuzzy relation based on the properties of max and min operations and the simultaneous updating of the prototype. The second optimization corresponds to an improvement of a cost function, in order to obtain a good quality of the solution of the decomposition problem.

KW - Fuzzy relation

KW - Gradient method

KW - Image decomposition

KW - Optimization

UR - http://www.scopus.com/inward/record.url?scp=18844425991&partnerID=8YFLogxK

U2 - 10.1016/j.asoc.2004.09.002

DO - 10.1016/j.asoc.2004.09.002

M3 - Article

AN - SCOPUS:18844425991

SN - 1568-4946

VL - 5

SP - 399

EP - 408

JO - Applied Soft Computing

JF - Applied Soft Computing

IS - 4

ER -

Efficient decomposition methods of fuzzy relation and their application to image decomposition

Abstract

Keywords

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