Self-adaptive dragonfly based optimal thresholding for multilevel segmentation of digital images
Dragonfly optimization (DFO) is a population based meta-heuristic optimization algorithm that simulates the static and dynamic swarming behaviors of dragonflies. The static swarm comprising less number of dragonflies in a small area for hunting preys, while the dynamic swarm with a large number of d...
Saved in:
| Main Authors: | Rakoth Kandan Sambandam, Sasikala Jayaraman |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2018-10-01
|
| Series: | Journal of King Saud University: Computer and Information Sciences |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157816301082 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation
by: Eman Mahmoud, et al.
Published: (2025-07-01) -
Adaptive two-threshold quantization and image segmentation based on the splitting and merging areas
by: O. M. Almiahi, et al.
Published: (2019-06-01) -
An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation
by: Liang Xiang, et al.
Published: (2025-05-01) -
The blueprint for survival: the blue dasher dragonfly as a model for urban adaptation
by: Ethan R. Tolman, et al.
Published: (2025-07-01) -
Dragonflies and Damselflies (Insecta: Odonata)
by: Seth Bybee
Published: (2005-10-01)