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GENETIC ALGORITHMS FOR POLYGONAL APPROXIMATION OF DIGITAL CURVES

机译:用于数字曲线的多边形逼近的遗传算法

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摘要

In this paper, three polygonal approximation approaches using genetic algorithms are proposed. The first approach approximates the digital curve by minimizing the number of sides of the polygon and the approximation error should be less than a prespecified tolerance value. The second approach minimizes the approximation error by searching for a polygon with a given number of sides. The third approach, which is more practical, determines the approximating polygon automatically without any given condition. Moreover, a learning strategy for each of t he proposed genetic algorithm is presented to improve the results. The experimental results show that the proposed approaches have better performances than those of existing methods.
机译:本文提出了三种使用遗传算法的多边形逼近方法。第一种方法是通过最小化多边形的边数来近似数字曲线,并且近似误差应小于预定的公差值。第二种方法是通过搜索具有给定边数的多边形来最小化近似误差。更实用的第三种方法是在没有任何给定条件的情况下自动确定近似多边形。此外,针对每种提出的遗传算法,提出了一种学习策略,以改善结果。实验结果表明,所提出的方法具有比现有方法更好的性能。

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