A genetic algorithm with chromosome-repairing for min - # and min - epsilon polygonal approximation of digital curves

作者：Wang Bin^*; Shu Huazhong; Luo Limin

来源：Journal of Visual Communication and Image Representation, 2009, 20(1): 45-56.

DOI：10.1016/j.jvcir.2008.10.001

• Genetic algorithms
• Chromosome repairing
• Digital curves
• Polygonal approximations
• Integral square error
• Optimization
• Split technique
• Merge technique

A genetic algorithm for solving min - epsilon polygonal approximation and min - # polygonal approximation is proposed in this paper. It combines traditional split-and-merge techniques with a novel chromosome-repairing scheme to cope with constraints. Due to this combination of techniques we call our new method SMCR. In this new scheme an infeasible solution cannot only be easily transformed into a feasible one, but also be optimized. The experimental results show that the proposed SMCR has higher performance than the other GA-based methods and some non-GA-based methods.

• 出版日期2009-1
• 单位东南大学