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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Study on detection of boats using satellite imagery for use on unmanned aerial vehicles




    Publication date :

    2017-11-01


    Size :

    474595 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles

    Kruber, Friedrich / Morales, Eduardo Sanchez / Chakraborty, Samarjit et al. | IEEE | 2020


    VEHICLE POSITION ESTIMATION WITH AERIAL IMAGERY FROM UNMANNED AERIAL VEHICLES

    Kruber, Friedrich / Morales, Eduardo Sánchez / Chakraborty, Samarjit et al. | British Library Conference Proceedings | 2020




    An Enhanced Viola-Jones Vehicle Detection Method From Unmanned Aerial Vehicles Imagery

    Xu, Yongzheng / Yu, Guizhen / Wu, Xinkai et al. | IEEE | 2017