计算机与数字工程2012，Vol.40Issue(2)：96-98,126,4.
基于KD-Tree搜索和SURF特征的图像匹配算法研究
Image Matching Algorithm Research Based on KD-Tree Search and SURF Features
杜振鹏 1李德华1
作者信息
- 1. 华中科技大学图像识别与人工智能研究所 武汉430074
- 折叠
摘要
Abstract
According to the problem of long search time in detecting and matching features of image matching, so in this paper, an image matching algorithm based on KD-Tree and SURF features is researched. Firstly extract SURF features of images and create feature vectors, then build KD-Trees for these feature vectors, finally complete the image matching work by calculating the nearest neighbor vector which is nearest to each feature vector. The experimental results express that, the speed of detecting features by SURF algorithm is 2-3 times faster than by SIFT algorithm; in comparison with global nearest search, approximate nearest neighbor searching based on KD-Tree has Less calculation, so in this way, the proposed algorithm improves matching speed.关键词
KD-Tree/SURF/图像匹配/特征提取/近似最近邻搜索Key words
KD-Tree, SURF, image matching, feature extraction, approximate nearest neighbor searching分类
信息技术与安全科学引用本文复制引用
杜振鹏,李德华..基于KD-Tree搜索和SURF特征的图像匹配算法研究[J].计算机与数字工程,2012,40(2):96-98,126,4.
