Study on detection of boats using satellite imagery for use on unmanned aerial vehicles
| Autor: | G. Santos Santiago, G. L. A. de Albuquerque, Joao B. D. Dantas, A. A. D. de Medeiros, B. R. F. da Silva, Pablo Javier Alsina, Marcelo B. Nogueira |
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| Rok vydání: | 2017 |
| Předmět: |
business.product_category
business.industry Computer science 010401 analytical chemistry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020206 networking & telecommunications 02 engineering and technology 01 natural sciences 0104 chemical sciences Support vector machine Histogram of oriented gradients Rocket Knowledge base Histogram 0202 electrical engineering electronic engineering information engineering Trajectory Satellite imagery Satellite Computer vision Artificial intelligence business |
| Zdroj: | LARS/SBR |
| DOI: | 10.1109/sbr-lars-r.2017.8215300 |
| Popis: | This work presents the development of a system that performs the detection of boats from aerial images acquired by satellites. This will serve as a knowledge base for the implementation of a system to be implemented in a fleet of unmanned aerial vehicle. The main purpose of the system is to detect ships that are in the risk zone of rocket trajectory launched from Barreira do Inferno Launch Center — CLBI. In previous work the authors proposed an algorithm to perform boat detection, however the results showed a high incidence of false positives. In order to improve those results, we propose the use of the Histogram of Oriented Gradients descriptor in candidate images followed by machine learning teachniques such as Suport Vector Machine and K Nearest Neighbours to classify them. To validate the system some experimental results are shown using satellite images, since the aerial vehicle is under constuctions and there is no image database yet. |
| Databáze: | OpenAIRE |
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