9 September 2014 Constructions detection from unmanned aerial vehicle images using random forest classifier and histogram-based shape descriptor
Bo Yu, Li Wang, Zheng Niu, Muhammd Shakir, Xiaoqi Liu
Author Affiliations +
Funded by: Major State Basic Research Development Program of China, China’s Special Funds for Major State Basic Research Project of China, Special Fund Research, National Natural Science Foundation of China
Abstract
Remotely sensed data, especially unmanned aerial vehicle images, provide more details about intensive ground objects. An algorithm with a solid capability to effectively handle this massive information is highly desired. The state-of-the-art algorithms proposed for building detection mainly focus only on buildings in use, ignoring those under construction. For buildings under construction, various types of soil are the main obstructions that impede building identification. Unmanned aerial vehicle images are used as experimental data for discriminating constructions (both in use and under construction) from other ground objects. A mask for potential constructions is created before the exact detection. A random forest classifier, together with a high dimensional textural feature, is used to remove soils that share similar texture characteristics with constructions. Experimental results suggest that our method can be widely used to detect construction (both in use and under construction) and has the ability to effectively handle heavy amounts of information from large-scale images with very high spatial resolution. It provides a method for soil exclusion from remotely sensed images with very high resolution.
© 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2014/$25.00 © 2014 SPIE
Bo Yu, Li Wang, Zheng Niu, Muhammd Shakir, and Xiaoqi Liu "Constructions detection from unmanned aerial vehicle images using random forest classifier and histogram-based shape descriptor," Journal of Applied Remote Sensing 8(1), 083554 (9 September 2014). https://doi.org/10.1117/1.JRS.8.083554
Published: 9 September 2014
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Cited by 4 scholarly publications.
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KEYWORDS
Unmanned aerial vehicles

Image processing

Shape analysis

Detection and tracking algorithms

Vegetation

Roads

Sensors

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