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Journal Article Horizon Detection in Maritime Images using Scene Parsing Network
Cited 28 time in scopus Share share facebook twitter linkedin kakaostory
Authors
C.Y. Jeong, H.S. Yang, K.D. Moon
Issue Date
2018-06
Citation
Electronics Letters, v.54, no.12, pp.760-762
ISSN
0013-5194
Publisher
IET
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1049/el.2018.0989
Abstract
A method for horizon detection in maritime scenes using a scene parsing network is proposed. First, each pixel from an input image is segmented into corresponding semantic categories using a scene parsing network, which relies on a deep neural network. Then, the boundary information related to the horizon and the sea is extracted. Scene segmentation allows the proposed method to identify the horizon, regardless of whether the boundary between the sea and sky is smooth or blurry, or whether the image contains many line elements like the horizon. Moreover, least squares and median filtering are iteratively used to retrieve an accurate estimation of the horizon line. Experimental results demonstrate the superior accuracy of the proposed method to identify the horizon when compared to state-of-the-art methods.
KSP Keywords
Deep neural network(DNN), Least Squares(LS), Median Filtering, Scene Parsing, Scene Segmentation, Semantic categories, accurate estimation, boundary information, horizon detection, state-of-The-Art