Abstract
In this paper, a new method is proposed for finding the suitable forced landing sites for UAVs. This approach does not have any limitations of the previous few researches done in this area. For finding the suitable landing sites, we first segment the aerial images based on classification using both color and texture features. Classification is performed based on k-nearest neighbor algorithm by incorporation of Gabor filters in HSV color space. Then, a geometric test is carried out for finding appropriately sized and shaped landing sites. Output images highlight the selected safe landing locations. Experimental results show the effectiveness of the proposed method.
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Dehshibi, M.M., Fahimi, M.S., Mashhadi, M. (2015). Vision-Based Site Selection for Emergency Landing of UAVs. In: Unger, H., Meesad, P., Boonkrong, S. (eds) Recent Advances in Information and Communication Technology 2015. Advances in Intelligent Systems and Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-19024-2_14
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DOI: https://doi.org/10.1007/978-3-319-19024-2_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19023-5
Online ISBN: 978-3-319-19024-2
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