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 image-chromosome 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.
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Di Martino, F., Sessa, S. (2007). A Genetic Algorithm Based on Eigen Fuzzy Sets for Image Reconstruction. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_43
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DOI: https://doi.org/10.1007/978-3-540-73400-0_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73399-7
Online ISBN: 978-3-540-73400-0
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