Sciweavers

ICPR
2010
IEEE

Efficient Polygonal Approximation of Digital Curves via Monte Carlo Optimization

13 years 5 months ago
Efficient Polygonal Approximation of Digital Curves via Monte Carlo Optimization
A novel stochastic searching scheme based on the Monte Carlo optimization is presented for polygonal approximation (PA) problem. We propose to combine the split-and-merge based local optimization and the Monte Carlo sampling, to give an efficient stochastic optimization scheme. Our approach, in essence, is a well-designed Basin-Hopping scheme, which performs stochastic hopping among the reduced energy peaks. Experiment results on various benchmarks show that our method achieves high-quality solutions with lower computational costs, and outperforms most of state-ofthe-art algorithms for PA problem
Xiuzhuang Zhou, Yao Lu
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where ICPR
Authors Xiuzhuang Zhou, Yao Lu
Comments (0)