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基于点空间特征的两种点匹配算法

, PP. 325-330

Keywords: 计算机视觉,点匹配,加权特征向量法,顺序匹配,距离向量

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Abstract:

通过讨论和分析经典特征向量匹配算法的基本原理和抗噪性能问题,提出2种新的点匹配算法:加权特征向量算法和顺序匹配算法.加权特征向量匹配算法通过对点集距离矩阵进行特征向量分解获得点集中点的特征向量,而后利用特征值对向量加权,通过比较点的加权特征向量相似性来获取匹配关系.顺序匹配算法避免了矩阵分解,直接对距离矩阵的距离向量进行排序,通过较有序的向量来获取匹配关系.这2种算法,解决了经典特征向量匹配算法中抗噪性能差和高斯参数选择的2个问题.实验结果表明,算法切实可行,文中结论正确.

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