A fuzzy hybrid method for image decomposition problem

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

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. © 2008 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Di Martino, F., Loia, V., & Sessa, S. (2008). A fuzzy hybrid method for image decomposition problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4974 LNCS, pp. 353–358). https://doi.org/10.1007/978-3-540-78761-7_37

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free