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دسته بندی:
پردازش تصویر - Image Processing
سال انتشار:
2017
عنوان انگلیسی مقاله:
Ship detection for visual maritime surveillance from non-stationary platforms
ترجمه فارسی عنوان مقاله:
تشخیص کشتی برای نظارت دریایی بصری از چارچوب بدون ایستگاه
منبع:
Sciencedirect - Elsevier - Ocean Engineering, 141 (2017) 53-63. doi:10.1016/j.oceaneng.2017.06.022
نویسنده:
Yang Zhang, Qing-Zhong Li⁎, Feng-Ni Zang
چکیده انگلیسی:
This paper presents a new ship target detection algorithm to achieve efficient visual maritime surveillance from
non-stationary surface platforms, e.g., buoys and ships, equipped with CCD cameras. In the proposed detector,
the three main steps including horizon detection, background modeling and background subtraction, are all
based on Discrete Cosine Transform (DCT). By exploiting the characteristics of DCT blocks, we simply extract
the horizon line providing an important cue for sea-surface modeling. The DCT-based feature vectors are
calculated as the sample input to a Gaussian mixture model which is effective in representing dynamic ocean
textures, such as waves, wakes and foams. Having modeled sea regions, we perform the ship detection using
background subtraction followed by foreground segmentation. Experimental results with various maritime
images demonstrate that the proposed ship detection algorithm outperforms the traditional techniques in terms
of both detection accuracy and real-time performance, especially for complex sea-surface background with large
waves.
Keywords: Ship detection | Visual maritime surveillance | Object detection | Gaussian mixture model | Discrete cosine transform
قیمت: رایگان
توضیحات اضافی:
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