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The research on nearest neighbor search algorithm based on vantage point tree

机译:基于Vantage Point树的最近邻南搜索算法研究

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The nearest neighbor search algorithm is an indispensable part of many image processing algorithms. In order to improve its performance, this paper proposes a similar nearest neighbor search algorithm combining multiple vantage point trees and improved pruning search methods. Firstly, when the vantage point tree is created, the vantage points are selected by selecting the points with the best degree of differentiation; Then, a new method of constructing vantage point forest is proposed to improve the nearest neighbor non-compact problem in the superior sub-tree; Finally, an improved pruning search method is proposed to find similar nearest neighbors, which reduces many unnecessary distance calculations. The experimental results show that the algorithm performance has been greatly improved in the data set size, returned the number of different neighbors, data dimension and the number of building trees.
机译:最近的邻居搜索算法是许多图像处理算法的不可或缺的一部分。为了提高其性能,本文提出了一种类似的最近邻居搜索算法,组合多个Vantage Point树和改进的修剪搜索方法。首先,当创建有利程度树时,通过选择具有最佳分化程度的点来选择优化点;然后,提出了一种构建有利点森林的新方法,以改善优越的子树中最近的邻居非紧凑问题;最后,提出了一种改进的修剪搜索方法来查找类似的最近邻居,这减少了许多不必要的距离计算。实验结果表明,在数据集大小中,算法性能大大提高,返回了不同邻居,数据维度和建筑物数量的数量。

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