Computer Science ›› 2019, Vol. 46 ›› Issue (6): 316-321.doi: 10.11896/j.issn.1002-137X.2019.06.048

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UAV Image Matching Algorithm Based on Improved SIFT Algorithm and Two-stage Feature Matching

SHAO Jin-da1, YANG Shuai1, CHENG Lin2   

  1. (College of Geomatics Science and Technology,Nanjing Tech University,Nanjing 210000,China)1
    (School of Transportation,Southeast University,Nanjing 210096,China)2
  • Received:2018-05-21 Published:2019-06-24

Abstract: Aiming at the problems in the matching process of UAV aerial images,such as long time,high cost and large amount of computation,this paper proposed an UAV image matching algorithm based on scale invariant feature transform scale invariant feature transform(SIFT) algorithm and geometrical algebraic method geometry algebra(GA) to achieve fast image feature extraction and feature matching.Firstly,the feature points are detected and described by using GA method and SIFT algorithms.Then,two-level feature matching is performed,fast library for approximate nearest neighbors (FLANN) algorithm is used to pre-matching the feature points and matching results is optimized according to the improved random sample consensus(RANSAC) algorithm.Experimental results show that compared with traditio-nal image matching algorithm,the proposed algorithm can locate more feature points accurately and improve the speed of image alignment process greatly,and it can save a lot of time for image matching of large drones.

Key words: FLANN rough matching, Geometry algebra, Improved RANSAC algorithm, SIFT algorithm, UAV image matching

CLC Number: 

  • TP391
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