We use an hybrid approach based on a genetic algorithm and on the gradient descent method in order to decompose an image. In the pre-processing phase the genetic algorithm is used for finding two suitable initial families of fuzzy sets that decompose R in accordance to the well known concept of Schein rank. These fuzzy sets are successively used in the descent gradient algorithm which determines the final fuzzy sets, useful for the reconstruction of the image. The experiments are executed on some images extracted from the the SIDBA standard image database.Abstract. We use an hybrid approach based on a genetic algorithm and on the gradient descent method in order to decompose an image. In the pre-processing phase the genetic algorithm is used for finding two suitable initial families of fuzzy sets that decompose R in accordance to the well known concept of Schein rank. These fuzzy sets are successively used in the descent gradient algorithm which determines the final fuzzy sets, useful for the reconstruction of the image. The experiments are executed on some images extracted from the the SIDBA standard image database.

A fuzzy hybrid method for image decomposition problem

SESSA, SALVATORE;F. DI MARTINO;
2008

Abstract

We use an hybrid approach based on a genetic algorithm and on the gradient descent method in order to decompose an image. In the pre-processing phase the genetic algorithm is used for finding two suitable initial families of fuzzy sets that decompose R in accordance to the well known concept of Schein rank. These fuzzy sets are successively used in the descent gradient algorithm which determines the final fuzzy sets, useful for the reconstruction of the image. The experiments are executed on some images extracted from the the SIDBA standard image database.Abstract. We use an hybrid approach based on a genetic algorithm and on the gradient descent method in order to decompose an image. In the pre-processing phase the genetic algorithm is used for finding two suitable initial families of fuzzy sets that decompose R in accordance to the well known concept of Schein rank. These fuzzy sets are successively used in the descent gradient algorithm which determines the final fuzzy sets, useful for the reconstruction of the image. The experiments are executed on some images extracted from the the SIDBA standard image database.
9783540787600
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/193807
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