Paper
19 September 2019 Analysis of different background subtraction methods applied on drone imagery under various weather conditions in the UAE region
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Abstract
The following paper presents a benchmarking study of the performance of thirty state of the art background subtraction algorithms. In this work, we test the performance of multiple background subtraction methods using drone imageries taken under various weather conditions in the UAE region. This is done by comparing the quality of the foreground mask that is extracted when using these algorithms. Visual Studio and MATLAB has been used to perform the comparison simulations, which would give us a comprehensive background subtraction study to indicate the advantages and disadvantages of each of the algorithms. The algorithms must be robust to stabilization errors, able to cope with insufficient information as a result from various weather conditions such as wind, haze and heat, and able to cope with dynamic backgrounds.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdullah Hasan AlSaadi, Issacniwas Swamidoss, Abdulrahman Almarzooqi, and Slim Sayadi "Analysis of different background subtraction methods applied on drone imagery under various weather conditions in the UAE region", Proc. SPIE 11169, Artificial Intelligence and Machine Learning in Defense Applications, 111690M (19 September 2019); https://doi.org/10.1117/12.2534644
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Cited by 1 scholarly publication.
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KEYWORDS
Detection and tracking algorithms

Target detection

MATLAB

Airborne remote sensing

Fuzzy logic

Cameras

Humidity

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