DocumentCode :
457242
Title :
Approximation of Digital Curves using a Multi-Objective Genetic Algorithm
Author :
Locteau, Hervé ; Raveaux, Romain ; Adam, Sébastien ; Lecourtier, Yves ; Héroux, Pierre ; Trupin, Eric
Author_Institution :
LITIS Labs., Rouen Univ.
Volume :
2
fYear :
0
fDate :
0-0 0
Firstpage :
716
Lastpage :
719
Abstract :
In this paper, a digital planar curve approximation method based on a multi-objective genetic algorithm is proposed. In this method, the optimization/exploration algorithm locates breakpoints on the digital curve by minimizing simultaneously the number of breakpoints and the approximation error. Using such an approach, the algorithm proposes a set of solutions at its end. The user may choose his own solution according to its objective. The proposed approach is evaluated on curves issued from the literature and compared successfully with many classical approaches
Keywords :
approximation theory; computational geometry; curve fitting; genetic algorithms; digital curves approximation; digital planar curve approximation; exploration algorithm; multiobjective genetic algorithm; optimization algorithm; Approximation algorithms; Approximation error; Approximation methods; Extremities; Genetic algorithms; Image processing; Optimization methods; Pattern recognition; Shape; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
ISSN :
1051-4651
Print_ISBN :
0-7695-2521-0
Type :
conf
DOI :
10.1109/ICPR.2006.276
Filename :
1699305
Link To Document :
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