[1]唐坤,韩斌.一种基于参考点距离的SIFT特征点匹配算法[J].智能系统学报,2015,10(3):376-380.[doi:10.3969/j.issn.1673-4785.201311020]
TANG Kun,HAN Bin.A SIFT matching algorithm based on the distance to reference point[J].CAAI Transactions on Intelligent Systems,2015,10(3):376-380.[doi:10.3969/j.issn.1673-4785.201311020]
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《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第3期
页码:
376-380
栏目:
学术论文—机器学习
出版日期:
2015-06-25
- Title:
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A SIFT matching algorithm based on the distance to reference point
- 作者:
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唐坤1, 韩斌2
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1. 东南大学 交通学院, 江苏 南京 210096;
2. 江苏科技大学 计算机科学与工程学院, 江苏 镇江 212000
- Author(s):
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TANG Kun1, HAN Bin2
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1. School of Transportation, Southeast University, Nanjing 210096, China;
2. School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212000, China
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- 关键词:
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SIFT; DRP算法; 特征点匹配; 最近邻; 参考点
- Keywords:
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scale invariant feature transform (SIFT); distance to reference point (DRP) algorithm; feature point matching; nearest neighbor; reference point
- 分类号:
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TP319
- DOI:
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10.3969/j.issn.1673-4785.201311020
- 文献标志码:
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A
- 摘要:
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针对SIFT特征点匹配时间消耗大的问题,提出了一种基于参考点距离的SIFT特征点匹配算法—DRP算法.该算法首先计算一次所有待匹配特征点到参考点之间的距离,对之进行快速排序并保存.然后计算待查询特征点到参考点的距离,并在已排序的距离中使用二分法搜索返回此距离的最近邻.最后以此最近邻为中心,在有限范围内搜索待查询特征点的近似最近邻.VGG实验室ACF图片库的测试结果表明,相比于经典的SIFT算法,DRP算法可以在不损失匹配效果的前提下,有效降低SIFT特征点匹配的时间消耗.
- Abstract:
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To address the high time cost of feature point matching in scale invariant feature transform (SIFT), a new SIFT feature point matching algorithm based on the distance to reference point—DRP algorithm is put forward. Firstly, distances from the reference point to every feature point to be matched is computed using DRP algorithm. Then, these distances computed previously is ordered and saved in a dataset named as distance of ordering. Next, distances from the reference point to the feature point to be queried is also computed. After that, the nearest neighbor of the distance in distance of ordering is retrieved with binary search and returned as index of center. Finally, the nearest neighbor of feature point to be queried is searched one by one in a certain range whose center is index of center. It is proven by experiment tested on ACF (affine covariant features) pictures from VGG(visual geometry group) laboratory that DRP algorithm can effectively decrease the time cost of SIFT feature points matching without loss of matching results compared with the classical SIFT algorithm.
备注/Memo
收稿日期:2013-11-28;改回日期:。
基金项目:国家自然科学基金资助项目(61374195);中央高校基本科研业务费专项资金资助项目;江苏省普通高校研究生科研创新计划资助项目(KYLX_0180).
作者简介:唐坤,男,1988年生,博士研究生,主要研究方向为数字图像处理、智能交通.韩斌,男,1968年生,教授,博士,主要研究方向为数字图像处理、智能检测、并行计算.
通讯作者:唐坤. E-mail: tkpaperzc@sina.cn.
更新日期/Last Update:
2015-07-15