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Spotted hyena optimizer with lateral inhibition for image matching

  • Qifang Luo
  • Jie Li
  • Yongquan ZhouEmail author
Article
  • 8 Downloads

Abstract

A hybrid spotted hyena optimizer (SHO) based on lateral inhibition (LI) is proposed, it has been applied to solve complication image matching problems. Lateral inhibition mechanism is applied for image pre-process to make intensity gradient in the image contrast enhanced and has the ability to enhance the characters of image, which is able to improve the accuracy of image matching. SHO is inspired from the behavior of social relationship and collaborative of spotted hyenas. This algorithm search for the global optimum mainly through four steps: prey, encircling, attacking prey, and searching prey. In the algorithm, the computation of search location is drastically reduced by incorporating of fitness calculation strategy for solving the real-life optimization problems. The proposed LI-SHO method for image matching mixed together the advantages of SHO and lateral inhibition mechanism. The experiment shows that the proposed algorithm based on lateral inhibition is more effective and feasible in image matching than the other comparing algorithm.

Keywords

Spotted hyena optimizer (SHO) Lateral inhibition (LI) Image matching Bio-inspired algorithm 

Notes

Acknowledgments

This work is supported by National Science Foundation of China under Grant No.61563008. Project of Guangxi University for Nationalities Science Foundation under Grant No. 2018GXNSFAA138146.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Information Science and EngineeringGuangxi University for NationalitiesNanningChina
  2. 2.Key Laboratory of Guangxi High Schools Complex System and Computational IntelligenceNanningChina
  3. 3.Department of Computer ScienceJinan UniversityGuangzhouChina

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