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Brightness correction and shadow removal for video change detection with UAVs

: Müller, Thomas; Erdnüß, Bastian


Dudzik, Michael C. (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Autonomous Systems: Sensors, Processing, and Security for Vehicles and Infrastructure 2019 : 15-16 April 2019, Baltimore, Maryland
Bellingham, WA: SPIE, 2019 (Proceedings of SPIE 11009)
ISBN: 978-1-5106-2683-6
ISBN: 978-1-5106-2684-3
Paper 1100906, 20 pp.
Conference "Autonomous Systems - Sensors, Processing, and Security for Vehicles and Infrastructure" <2019, Baltimore/Md.>
Conference Paper
Fraunhofer IOSB ()
unmanned aerial vehicles (UAV); video surveillance; change detection; shadow detection; shadow removal; brightness correction; improvised explosive device (IED); Counter-IED

Unmanned aerial vehicles (UAVs) on patrol that recognize scene changes are a powerful instrument in a lotof surveillance and reconnaissance applications, e.g., protection of convoys from improvised explosive devices(IEDs) by early detecting deployment traces, intruder or manipulation detection for real estates and militarycamps, or danger recognition and assessment in disaster monitoring. For that purpose, a visual-optical camerarecords video streams in which an automatic video change detection computes relevant or suspicious changesbetween two patrols. The main challenge is to identify true scene changes, i.e. to filter out changes caused bycamera brightness variations, illumination changes due to cloudiness or time of day, or varying shadows cast byclouds or scene objects. Different partly overlapping or orthogonal solutions for all that, like chromatic adaptation, local mean adjustment, retinex, intensity equalization, and CIE Lab shadow removal, are evaluated andadvantages/disadvantages are compared. Finally, the optimal method selection and combination is determinedin order to maximize the change detection performance. Depicted results document the reached progress.