By normalizing the values of its pixels, any image is interpreted as a fuzzy relation whose the greatest eigen fuzzy set with respect to the max−min composition and the smallest eigen fuzzy set with respect to the min−max composition are used in a genetic algorithm for image reconstruction scopes. Image-chromosomes form the population and a fitness function based on the above eigen fuzzy sets of each imagechromosome and of the related original image is used for performing the selection operator. The reconstructed image is the image-chromosome with the highest value of fitness.
A Genetic Algorithm Based on Eigen Fuzzy Sets for Image Reconstruction / Sessa, Salvatore; DI MARTINO, F.. - STAMPA. - 4578:(2007), pp. 342-348. (Intervento presentato al convegno 7th WILF tenutosi a Camogli, Italia nel 7-10 luglio 2007) [10.1007/978-3-540-73400-0].
A Genetic Algorithm Based on Eigen Fuzzy Sets for Image Reconstruction
SESSA, SALVATORE;F. DI MARTINO
2007
Abstract
By normalizing the values of its pixels, any image is interpreted as a fuzzy relation whose the greatest eigen fuzzy set with respect to the max−min composition and the smallest eigen fuzzy set with respect to the min−max composition are used in a genetic algorithm for image reconstruction scopes. Image-chromosomes form the population and a fitness function based on the above eigen fuzzy sets of each imagechromosome and of the related original image is used for performing the selection operator. The reconstructed image is the image-chromosome with the highest value of fitness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
