uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
Runway detection in LWIR video: Real time image processing and presentation of sensor data
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
2016 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Runway detection in long wavelength infrared (LWIR) video could potentially increase the number of successful landings by increasing the situational awareness of pilots and verifying a correct approach. A method for detecting runways in LWIR video was therefore proposed and evaluated for robustness, speed and FPGA acceleration.

The proposed algorithm improves the detection probability by making assumptions of the runway appearance during approach, as well as by using a modified Hough line transform and a symmetric search of peaks in the accumulator that is returned by the Hough line transform.

A video chain was implemented on a Xilinx ZC702 Development card with input and output via HDMI through an expansion card. The video frames were buffered to RAM, and the detection algorithm ran on the CPU, which however did not meet the real-time requirement. Strategies were proposed that would improve the processing speed by either acceleration in hardware or algorithmic changes.

Place, publisher, year, edition, pages
2016. , 54 p.
UPTEC F, ISSN 1401-5757 ; 16044
Keyword [en]
LWIR, FPGA, Zynq, Runway, Hough transform, Real-time
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:uu:diva-300690OAI: oai:DiVA.org:uu-300690DiVA: diva2:951922
External cooperation
Saab Group
Educational program
Master Programme in Engineering Physics
2016-06-27, Ångström 11167, Lägerhyddsvägen 1, Uppsala, 22:04 (Swedish)
Available from: 2016-08-11 Created: 2016-08-10 Last updated: 2016-08-11Bibliographically approved

Open Access in DiVA

Master Thesis - Erasmus Cedernaes(2749 kB)36 downloads
File information
File name FULLTEXT01.pdfFile size 2749 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
Division of Visual Information and Interaction
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 36 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 351 hits
ReferencesLink to record
Permanent link

Direct link