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Polygonal approximation of digital curves using genetic algorithms

机译:使用遗传算法的数字曲线的多边形逼近

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摘要

We present a method to approximate a digital curve with a straight line sequence. The curve approximation curve has been posed as an optimization problem, and a genetic algorithm is used to solve such a problem. The proposed approach outputs a set of ending points for the line segments used to encode the resulting polygonal approximation. We have tested our method with a curve dataset composed of 11 open and closed curves. The results show that the proposed method performs qualitatively well on the test dataset. We show also quantitative measures of the similarity between the original input curve and the results of the genetic algorithm-based optimization process.
机译:我们提出一种用直线序列近似数字曲线的方法。曲线逼近曲线已被提出为优化问题,并且使用遗传算法来解决该问题。所提出的方法为用于编码所得的多边形近似的线段输出一组端点。我们已经用包含11条打开和闭合曲线的曲线数据集测试了我们的方法。结果表明,该方法在测试数据集上的定性性能良好。我们还显示了原始输入曲线与基于遗传算法的优化过程结果之间相似性的定量度量。

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