Treffer: Image‐based locating and guiding for unmanned aerial vehicles using scale invariant feature transform, speeded‐up robust features, and oriented fast and rotated brief algorithms.

This study provides a method for determining the location information from a photograph taken by an Unmanned Aerial Vehicle (UAV). In today's defense industry, the goal is to design a reliable navigation system that can operate even when the Internet and GPS systems are unavailable. In the proposed system, it is expected that there is an image database in which each image has its own metadata in JavaScript Object Notation format that defines the geolocation information for the corresponding image. In real‐time, UAV flies captures an image and uses a matching algorithm to compare it with each and every photo in the database. The image with the highest match rate in the database and its metadata is returned. The UAV extracts its own location information from the metadata. For image matching, Scale Invariant Feature Transform, Speeded‐Up Robust Features, and Oriented FAST and Rotated BRIEF algorithms are used. The proposed system is tested and evaluated by using a real‐world dataset obtained from Flickr's city images. The proposed approach is proved to work with a success rate of 97.14%. [ABSTRACT FROM AUTHOR]

Copyright of Concurrency & Computation: Practice & Experience is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)