Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

## Image database of low-altitude UAV flights with flight condition-logged for photogrammetry, remote sensing, and computer vision

• Author(s):
• DOI:

$16.00 (plus tax if applicable) ##### Buy Knowledge Pack 10 chapters for$120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:

Imaging and Sensing for Unmanned Aircraft Systems: Volume 2: Deployment and Applications — Recommend this title to your library

## Thank you

The growth in the number of aerial images available is stimulating research and development of computational tools capable of extracting information from these image databases. However, developing a new computer vision (CV) software is complicated because many factors influence the extraction of information from aerial images, such as lighting, flight altitude, and optical sensors. The CV has been incorporated in most modern machines such as autonomous vehicles and industrial robots. The aim is to produce a high-quality image database of low-altitude Unmanned Aerial Vehicle (UAV) flights with flight condition-logged for photogrammetry, remote sensing, and CV. This work resulted in a collection of aerial images in the visible and thermal spectrum, and this set of images was captured in different schedules of the day, altitudes of flight, times of the year. The cameras are synchronised with the UAVs autopilot, and they were spatially and spectrally characterised in the laboratory. This research makes available low altitude aerial images of a region in Brazil to all community, with the precise flight and capture information, as well as additional features such as ground truth and georeferenced mosaic. Examples of the use of the database are shown for mosaic generation and development of CV algorithms for autonomous navigation of UAVs [1,2]. Furthermore, this database will serve as a benchmark for the development of the CV algorithms suited for autonomous navigation by images.

Chapter Contents:

• 5.1 Introduction
• 5.1.1 Image processing system for UAVs
• 5.2 The aerial image database framework
• 5.2.1 Database requirements
• 5.2.2 Database design
• 5.3 Image capture process
• 5.4 Results
• 5.4.1 Images collected
• 5.5 Use of the image database
• 5.5.1 Mosaics
• 5.5.2 Development of CV algorithms
• 5.6 Conclusion and future works
• Acknowledgements
• References

Preview this chapter:

Image database of low-altitude UAV flights with flight condition-logged for photogrammetry, remote sensing, and computer vision, Page 1 of 2

| /docserver/preview/fulltext/books/ce/pbce120g/PBCE120G_ch5-1.gif /docserver/preview/fulltext/books/ce/pbce120g/PBCE120G_ch5-2.gif

### Related content

content/books/10.1049/pbce120g_ch5
pub_keyword,iet_inspecKeyword,pub_concept
6
6
This is a required field