DocumentCode :
1562240
Title :
Automatic sensor registration using stochastic optimization methods
Author :
Jian, Tung ; Ji-Hong, Zhu ; Zeng-qi, Sun
Author_Institution :
Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
Volume :
5
fYear :
2004
Firstpage :
3899
Abstract :
Sensor image registration is one of important problems in sensor fusion, it is the task of finding the correct mapping of one sensor image onto another. In this paper, the sensor image registration problem is approached as a optimization problem, then an appropriate fitness function is proposed to evaluate the mapping parameter set and several optimization methods (genetic algorithms, simulated annealing, hybrid strategy GASA) are adopted to solve this problem automatically. The experiment indicates the feasibility of the registration methods which are insensitive to noise. Among them, GASA shows good performance because of its rapid convergence.
Keywords :
convergence; genetic algorithms; image registration; image sensors; sensor fusion; simulated annealing; stochastic processes; automatic sensor registration; genetic algorithms; hybrid strategy GASA; rapid convergence; sensor fusion; sensor image mapping; sensor image registration; simulated annealing; stochastic optimization methods; Computer science; Convergence; Genetic algorithms; Image registration; Image sensors; Optimization methods; Sensor fusion; Simulated annealing; Stochastic processes; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
Type :
conf
DOI :
10.1109/WCICA.2004.1342225
Filename :
1342225
Link To Document :
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