中文

Journal of Shanghai University（Natural Science Edition） ›› 2017, Vol. 23 ›› Issue (1): 47-55.doi: 10.3969/j.issn.1007-2861.2016.07.018

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Sea-sky line detection based on structured forests edge detection and Hough transform

XU Liangyu1, MA Lukun1, XIE Xie1, PENG Yan1, PENG Yanqing2, CUI Jianxiang1   

  1. 1. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China;
    2. College of Sciences, PLA University of Science and Technology, Nanjing 210007, China
  • Received:2016-12-29 Online:2017-02-28 Published:2017-02-28

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Abstract:

The sea-sky line is an important feature in the sea-surface environment image, and detection of the sea-sky line is essential in dividing the sea and sky, and detecting the coastline area and objects. This paper provides a method to detect the sea-sky line using structured forests edge detection and Hough transform. The method uses a Gaussian low-pass filter to reduce the influence of regional textures such as wave texture and light reflection. A trained structured random decision forest is then used to label each pixel, and binarize it to determine whether it belongs to an edge or not. Hough transform is used to fit the sea-sky line more accurately. Experimental results show that this method can neglect clutter edge, greatly improve edge detection, and effectively extract sea-sky lines from a complicated sea-sky background with high robustness and accuracy.

Key words:  decision tree ,  edge detection ,  Hough transform,  structured random forest , sea-sky line detection