DocumentCode :
2105096
Title :
The gray scale matching algorithm based on a new hybrid PSO
Author :
Hongluan Zhao ; Zunyi Xu ; Guoyong Han ; Yi Liu
Author_Institution :
Dept. of Comput. Sci. & Technol., Shandong Jianzhu Univ., Jinan, China
fYear :
2012
fDate :
9-11 Nov. 2012
Firstpage :
1012
Lastpage :
1016
Abstract :
The quick matching is researched between the template image and reference image with rotating and angle zoom. A new hybrid algorithm of differential evolution (DE) and particle swarm optimization algorithm(PSO) is put forward in order to improve the local search ability and precocious phenomena of PSO. Using the information exchange mechanism, two groups of population evolve collaboratively with DE and PSO respectively. Further, here employs the current developments of the two heuristic algorithms. Then the fitness function of the relationship is discussed between the template matching algorithm and the new algorithm, combined with the matching model optimization search and superior performance of PSO. Simulations are done to illustrate the signilicant and effective impact of this new algorithm, showing its efficiency and accuracy.
Keywords :
evolutionary computation; image matching; search problems; differential evolution; fitness function; gray scale matching algorithm; hybrid PSO; hybrid algorithm; local search ability; matching model optimization search; particle swarm optimization algorithm; quick matching; reference image; template image; DE; PSO; gray scale; matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Technology (ICCT), 2012 IEEE 14th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-2100-6
Type :
conf
DOI :
10.1109/ICCT.2012.6511347
Filename :
6511347
Link To Document :
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