Metaheuristic Algorithms for Image Segmentation: Theory and Applications

This book presents a study of the most important methods of image segmentation and how they are extended and improved using metaheuristic algorithms. The segmentation approaches selected have been extensively applied to the task of segmentation (especially in thresholding), and have also been implem...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Oliva, Diego (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Abd Elaziz, Mohamed (http://id.loc.gov/vocabulary/relators/aut), Hinojosa, Salvador (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Studies in Computational Intelligence, 825
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Optimization
  • Metaheuristic optimization
  • Image processing
  • Image Segmentation using metaheuristics
  • Multilevel thresholding for image segmentation based on metaheuristic Algorithms
  • Otsu's between class variance and the tree seed algorithm
  • Image segmentation using Kapur's entropy and a hybrid optimization algorithm
  • Tsallis entropy for image thresholding
  • Image segmentation with minimum cross entropy
  • Fuzzy entropy approaches for image segmentation
  • Image segmentation by gaussian mixture
  • Image segmentation as a multiobjective optimization problem
  • Clustering algorithms for image segmentation
  • Contextual information in image thresholding.