Computer Science ›› 2019, Vol. 46 ›› Issue (6): 328-333.doi: 10.11896/j.issn.1002-137X.2019.06.050

Previous Articles    

Image Matching Method Combining Hybrid Simulated Annealing and Antlion Optimizer

ZHANG Huan-long, GAO Zeng, ZHANG Xiu-jiao, SHI Kun-feng   

  1. (College of Electric and Information Engineering,Zhengzhou University of Light Industry,Zhengzhou 450002,China)
  • Received:2018-04-20 Published:2019-06-24

Abstract: Aiming at low matching efficiency and accuracy of traditional swarm optimization algorithms in image matching,this paper proposed an image matching method combining hybrid simulated annealing(SA) and ant lion optimizer(ALO).In this method,the ALO algorithm is applied to image matching for the first time,and the boundary shrinkage mechanism and the search method of the interaction between ant and antlion are exploited to improve the matching efficiency and accuracy.Then,on the basis of making use of the rule of partial embedding criterion,the simulated annealing mechanism is introduced if the matching result falls into local optimum.Besides,the Lévy flight and the Metropolis criterion are utilized to ensure the algorithm run beyond the local optimum,thus improving the optimization performance and matching accuracy.Otherwise,ALO search strategy is directly used to complete image matching.The experimental results demonstrate fast matching speed and high matching accuracy of the proposed method.

Key words: Image matching, Ant lion optimizer, Simulated annealing, Swarm optimization

CLC Number: 

  • TP391.41
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