00 Acta Scientific | International Open Library | Open Access Journals Publishing Group

Acta Scientific Computer Sciences

Research Article Volume 2 Issue 12

Application of the Pigeon Method to the Classification of Captured Data

Yasmine Benyettou* and Hadria Fizazi

University of Sciences and Technology of Oran, USTO, Algeria

*Corresponding Author: Yasmine Benyettou, University of Sciences and Technology of Oran, USTO, Algeria.

Received: September 24, 2020; Published: November 18, 2020

×

Abstract

  This paper presents a method to increase the classification performance of satellite images by swarm intelligence. Traditional statistical classifiers have limitations in solving complex classification problems due to their harsh assumptions because these methods only examine spectral variance by ignoring the spatial distribution of pixels corresponding to land cover classes and the correlation between the different bands. An optimization algorithm inspired by the behavior of pigeons is applied and has been used in various fields such as image restoration, planning of the trajectories of aerial robots. In our case, the basic idea is: Davies-Bouldin (DBI) is used as a fitness function. The iterative optimization process is carried out by the pigeon optimization algorithm. In this process, the fitness function matches the coordinate of the pigeon in optimizing the problem. The best result is obtained when the pigeon finds the best overall position. This method converts the problem of finding the optimal solution to the problem of solving multidimensional variables and efficiently optimizes the result. In order to verify the feasibility and accuracy of the supervised classification, the K-means bisecting technique and the deep learning method were implemented. The results of the comparison indicate that the method based on the inspired pigeon optimization is effective with a good classification rate equal to 95.60%, an accuracy rate of 84.70% in a reduced execution time of 19.15 dry. The results of the calculation also show that the proposed PIO algorithm can effectively improve the speed of convergence, and the superiority of the overall search.

Keywords: Pigeon Inspired Optimization (PIO) Algorithm; K-Means Bisecting; Deep Learning; Satellite Image; Classification

×

References

  1. U Maulik and D. Chakraborty. “Remote Sensing Image Classification: A survey of support-vector-machine-based advanced techniques”. IEEE Geoscience and Remote Sensing Magazine1 (2017): 33‑52.
  2. A M Hannane and H Fizazi. “Supervised images classification using metaheuristics”. Mathematical and Computer Modelling (2016): 7.
  3. N Liu., et al. “Exploiting Convolutional Neural Networks With Deeply Local Description for Remote Sensing Image Classification”. IEEE Access 6 (2018): 11215-11228.
  4. G Cheng., et al. “When Deep Learning Meets Metric Learning: Remote Sensing Image Scene Classification via Learning Discriminative CNNs”. IEEE Transactions on Geoscience and Remote Sensing 5 (2018): 2811-2821.
  5. D Ienco., et al. “Land Cover Classification via Multitemporal Spatial Data by Deep Recurrent Neural Networks”. IEEE Geoscience and Remote Sensing Letters10 (2017): 1685-1689.
  6. H M Ahmed., et al. “Hybrid gray wolf optimizer-artificial neural network classification approach for magnetic resonance brain images”. Applied Optics7 (2018): B25.
  7. S Sharma and K M Buddhiraju. “Spatial-spectral ant colony optimization for hyperspectral image classification”. International Journal of Remote Sensing9 (2018).
  8. H Duan and X Wang, “Echo State Networks With Orthogonal Pigeon-Inspired Optimization for Image Restoration”. IEEE Transactions on Neural Networks and Learning Systems 11 (2016): 2413-2425.
  9. H Duan and P Qiao. “Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning”. International Journal of Intelligent Computing and Cybernetics1 (2014).
  10. W Liu., et al. “An Improved Otsu Multi-Threshold Image Segmentation Algorithm Based on Pigeon-Inspired Optimization”. in 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), Beijing, China (2018): 1-5.
  11. C Davison., et al. “Magnetoreception and its trigeminal mediation in the carrier pigeon”. Nature7016 (2004): 508-511.
  12. Q Luo and H Duan. “Distributed Drone Flocking Control Based on Hierarchical Carrier Pigeon Strategies”. Aerospace Science and Technology 70 (2017): 257-264.
  13. H Liu., et al. “An Improved Pigeon-Inspired Optimization Algorithm and Its Application in Parameter Inversion”. Symmetry10 (2019): 1291.
  14. AL Bolaji., et al. “Adaptation of Binary Pigeon-Inspired Algorithm for Solving Multidimensional Knapsack Problem”. in Soft Computing: Theories and Applications 583, M. Pant, K. Ray, T. K. Sharma, S. Rawat, and A. Bandyopadhyay, Eds. Singapore: Springer Singapore (2018): 743-751.
  15. Y Zhong., et al. “Discrete pigeon-inspired optimization algorithm with Metropolis acceptance criterion for large-scale traveling salesman problem”. Swarm and Evolutionary Computation 48 (2019): 134-144.
×

Citation

Citation: Yasmine Benyettou and Hadria Fizazi. “Application of the Pigeon Method to the Classification of Captured Data". Acta Scientific Computer Sciences 2.12 (2020): 27-35.




Metrics

Acceptance rate35%
Acceptance to publication20-30 days

Indexed In




News and Events


  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is September 30, 2021.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of “Best Article of the Issue”.
  • Welcoming Article Submission
    Acta Scientific delightfully welcomes active researchers for submission of articles towards the upcoming issue of respective journals.
  • Contact US