Szczegóły publikacji
Opis bibliograficzny
Embedded vision system for automated drone landing site detection / Patryk Frączek, Andre Mora, Tomasz KRYJAK // W: Computer vision and graphics : international conference : ICCVG 2018 : Warsaw, Poland, September 17–19, 2018 : proceedings / eds. Leszek J. Chmielewski [et al.]. — [Cham] : Springer International Publishing, cop. 2018. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 11114. Image Processing, Computer Vision, Pattern Recognition, and Graphics). — ISBN: 978-3-030-00691-4; e-ISBN: 978-3-030-00692-1. — S. 397–409. — Bibliogr. s. 408–409, Abstr.
Autorzy (3)
- AGHFrączek Patryk
- Mora Andre
- AGHKryjak Tomasz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 116985 |
|---|---|
| Data dodania do BaDAP | 2018-10-16 |
| Tekst źródłowy | URL |
| DOI | 10.1007/978-3-030-00692-1_35 |
| Rok publikacji | 2018 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computer Vision and Graphics 2018 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
This paper presents an embedded video subsystem used to classify the terrain, based on an image from a camera located under the drone, for the purpose of an automatic landing system. Colour and texture features, as well as decision trees and support vector machine classifiers were analysed and evaluated. The algorithm was supported with a shadow detection module. It was evaluated on 100 test cases and achieved over 80% performance. The designed video system was implemented on two embedded platforms – a Zynq SoC (System on Chip – Field Programmable Gate Array + ARM processor system) and a Jetson GPU (Graphic Processing Unit + ARM processor system). The performance achieved on both architectures is compared and discussed.
