<abstract xmlns="http://www.w3.org/1999/xhtml"><p>With the development of communication network and computer software and hardware technology, especially the emergence of high-precision and high-resolution image sensors, the photography and measurement technology of aerial image have played an increasingly important role in today's geological survey. The traditional aeronautical measurement is carried out by a large manned aircraft. The collected measurement information has a large capacity and a wide shooting range, which is suitable for large-area operations. This type of measurement requires high hardware requirements and is expensive, and it is not suitable for small areas. UAV aerial measurement system is used to measure the small areas, UAV is in small size, with great flight fluctuation, but the data image collected is not accurate enough. In this paper, the common algorithms of image fast matching are compared to conduct in-depth research on gray-level matching and feature-based matching, and SIFT feature matching algorithm based on feature matching is proposed to obtain the measurement image as consistent as possible with the actual scene. The main features of the object to be measured can be obtained through the actual surface area image measurement test, which is of practical significance in the practical low-altitude small area surveying and mapping.</p></abstract>

With the development of communication network and computer software and hardware technology, especially the emergence of high-precision and high-resolution image sensors, the photography and measurement technology of aerial image have played an increasingly important role in today's geological survey. The traditional aeronautical measurement is carried out by a large manned aircraft. The collected measurement information has a large capacity and a wide shooting range, which is suitable for large-area operations. This type of measurement requires high hardware requirements and is expensive, and it is not suitable for small areas. UAV aerial measurement system is used to measure the small areas, UAV is in small size, with great flight fluctuation, but the data image collected is not accurate enough. In this paper, the common algorithms of image fast matching are compared to conduct in-depth research on gray-level matching and feature-based matching, and SIFT feature matching algorithm based on feature matching is proposed to obtain the measurement image as consistent as possible with the actual scene. The main features of the object to be measured can be obtained through the actual surface area image measurement test, which is of practical significance in the practical low-altitude small area surveying and mapping.

Research and Realization on the key technology of Motion Image Matching Based on UAV

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

With the development of communication network and computer software and hardware technology, especially the emergence of high-precision and high-resolution...

Content of Check	Calibration Value	Remark
x0	-0.008214mm
y0	-0.003216mm	the element of camera internal azimuth
f(focal distance)	10.41234
k1 (Radial distortion factor)	2.12E-10	the coefficient of radial distortion
k2(the factor of radial distortion)	-8.14E-18
p1 (the factor of eccentricity distortion)	3.14E-7	Tangential distortion coefficient
p2 (the factor of eccentricity distortion)	-1.42E-7

	SIFT+BFMatch
Image extraction point	33092/30012
Time to generate the descriptor	178340ms
Match the time	278731ms
Threshold extraction points	16782
Filter after mismatched points	9783

Research and Realization on the key technology of Motion Image Matching Based on UAV

Data publikacji: 14 paź 2019

Zakres stron: 1 - 6

DOI: https://doi.org/10.21307/ijanmc-2019-014

Słowa kluczowe
UAV, Moving Image, Feature Detection, Image Matching, Image Pre-Processing

© 2018 Yuri Shebzukhov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

THE CALIBRATION RESULTS OF SONY RX100 CAMERA

FEATURES MATCHING PERFORMANCE TABLE

Research and Realization on the key technology of Motion Image Matching Based on UAV

Data publikacji: 14 paź 2019

Zakres stron: 1 - 6

DOI: https://doi.org/10.21307/ijanmc-2019-014

Słowa kluczoweUAV, Moving Image, Feature Detection, Image Matching, Image Pre-Processing

© 2018 Yuri Shebzukhov et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

THE CALIBRATION RESULTS OF SONY RX100 CAMERA

FEATURES MATCHING PERFORMANCE TABLE

Słowa kluczowe
UAV, Moving Image, Feature Detection, Image Matching, Image Pre-Processing