一种提高SIFT算法匹配效率的方法

Daixian Zhu, Xiaohua Wang
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引用次数: 6

摘要

由于SIFT (scale Invariant Feature Transform,尺度不变特征变换)描述子具有良好的尺度、旋转、光照不变性,因此常用于图像匹配。但其算法复杂,计算时间长。为了提高SIFT特征匹配算法的效率,提出了降低相似测度匹配代价的方法。用街区距离和棋盘距离的线性组合代替欧氏距离,利用局部特征的结果减少计算中的特征点。实验结果表明,该算法在降低时间复杂度的同时,保持了图像的鲁棒性,提高了图像匹配效率。关键词:特征匹配;特征提取;筛选;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method of Improving SIFT Algorithm Matching Efficiency
Due to the good invariance of scale, rotation, illumination, SIFT (Scale Invariant Feature Transform) descriptor is commonly used in image matching. but its algorithm is complicated and computation time is long. To improve SIFT feature matching algorithm efficiency, the method of reducing similar measure matching cost is mentioned. Euclidean distance is replaced by the linearcombination of cityblock distance and chessboard distance, and reduce character point in calculating with results of part feature. The experimental results show that the algorithm can reduce the rate of time complexity and maintain robust quality at the same time, image matching efficiency is improved. Keywords-feature matching ; feature extraction; SIFT;
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