UAV Image Matching Method Integrating SIFT Algorithm and Detection Model Optimization

Sha GAO; Xi-ping YUAN; Shu GAN; Lin HU; Rui BI; Rao-bo LI; Wei-dong LUO

doi:10.3964/j.issn.1000-0593(2022)05-1497-07

Spectroscopy and Spectral Analysis, Volume. 42, Issue 5, 1497(2022)

UAV Image Matching Method Integrating SIFT Algorithm and Detection Model Optimization

Sha GAO1;... Xi-ping YUAN1; 3;, Shu GAN1; 2; *;, Lin HU1;, Rui BI1;, Rao-bo LI1; and Wei-dong LUO1; |Show fewer author(s)

Author Affiliations

1. School of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China

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Figures & Tables(7)

Fig. 1. Flow chart of UAV image matching

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Fig. 2. Extreme value detection of Gaussian difference function

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Fig. 3. Experimental image data

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Table 1. Statistics on the number and length of image feature point extraction by different algorithms

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Table 1. Statistics on the number and length of image feature point extraction by different algorithms

image pair	SIFT		SURF		BRISK		ORB		KAZE
image pair	Feature points	Times /ms	Feature points	Times /ms	Feature points	Times /ms	Feature points	Times /ms	Feature points	Times /ms
Fig A Fig B	63 570 69 869	2 950.58	29 791 35 970	954.61	33 367 32 242	36 933.4	14 875 14 886	461.37	32 314 39 112	6 634.32

Table 2. Secondary screening of matched point pairs based on Mahalanobis distance and NNDR model

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Table 2. Secondary screening of matched point pairs based on Mahalanobis distance and NNDR model

image pair	SIFT+		SURF+		BRISK+		ORB+		KAZE+
image pair	Feature points	Times /ms	Feature points	Times /ms	Feature points	Times /ms	Feature points	Times /ms	Feature points	Times /ms
Fig A Fig B	25 040 23 984	899.72	5 380 5 163	109.55	11 585 10 888	392.45	10 827 10 417	200.16	3 520 3 096	106.63

Table 3. Statistics related to image feature point matching by different algorithms
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Table 3. Statistics related to image feature point matching by different algorithms
image
pair SIFT+ SURF+ BRISK+ ORB+ KAZE+
Inliers matched Inliers matched Inliers matched Inliers matched Inliers matched
Fig(A-B) 7 360 8 756 1 258 1 695 2 064 3 000 1 590 2 292 1 171 1 506

Table 4. Statistics of correct extraction rate and RMSE rate of image feature points by different algorithms
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Table 4. Statistics of correct extraction rate and RMSE rate of image feature points by different algorithms
image
pair SIFT+ SURF+ BRISK+ ORB+ KAZE+
Accuracy RMSE Accuracy RMSE Accuracy RMSE Accuracy RMSE Accuracy RMSE
Fig(A-B) 0.841 0.85 0.742 0.91 0.688 1.22 0.694 1.14 0.773 0.86

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Sha GAO, Xi-ping YUAN, Shu GAN, Lin HU, Rui BI, Rao-bo LI, Wei-dong LUO. UAV Image Matching Method Integrating SIFT Algorithm and Detection Model Optimization[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1497

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Paper Information

Category: Research Articles

Received: Apr. 22, 2021

Accepted: --

Published Online: Nov. 10, 2022

The Author Email:

DOI:10.3964/j.issn.1000-0593(2022)05-1497-07

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Statistics on the number and length of image feature point extraction by different algorithms

Table 1. Statistics on the number and length of image feature point extraction by different algorithms

Table 2. Secondary screening of matched point pairs based on Mahalanobis distance and NNDR model

Table 2. Secondary screening of matched point pairs based on Mahalanobis distance and NNDR model

Table 3. Statistics related to image feature point matching by different algorithms

Table 3. Statistics related to image feature point matching by different algorithms

Table 4. Statistics of correct extraction rate and RMSE rate of image feature points by different algorithms

Table 4. Statistics of correct extraction rate and RMSE rate of image feature points by different algorithms

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