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An Improved Ant Colony Matching by Using Discrete Curve Evolution

机译:利用离散曲线演化的改进蚁群匹配算法

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摘要

In this paper we present an improved Ant Colony Optimization (ACO) for contour matching, which can be used to match 2D shapes. Discrete Curve Evolution (DCE) technique is used to simplify the extracted contour. In order to find the best correspondence between shapes, the match process is formulated as a Quadratic Assignment Problem (QAP) and resolved by using Ant Colony Optimization (ACO). The experimental results justify that Discrete Curve Evolution (DCE) performs better than the previous Constant Sampling (CS) technique which has been selected for the ACO matching.
机译:在本文中,我们提出了一种用于轮廓匹配的改进蚁群优化(ACO),可用于匹配2D形状。离散曲线演化(DCE)技术用于简化提取的轮廓。为了找到形状之间的最佳对应关系,将匹配过程公式化为二次分配问题(QAP)并使用蚁群优化(ACO)进行求解。实验结果证明,离散曲线演化(DCE)的性能优于以前为ACO匹配选择的恒定采样(CS)技术。

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