基于结构森林边缘检测和Hough变换的海天线检测

doi:10.3969/j.issn.1007-2861.2016.07.018

上海大学学报(自然科学版) ›› 2017, Vol. 23 ›› Issue (1): 47-55.doi: 10.3969/j.issn.1007-2861.2016.07.018

基于结构森林边缘检测和Hough变换的海天线检测

徐良玉¹, 马录坤¹, 谢燮¹, 彭艳¹, 彭艳青², 崔建祥¹

1. 上海大学机电工程与自动化学院, 上海200072; 2. 中国人民解放军理工大学理学院, 南京210007

收稿日期:2016-12-29 出版日期:2017-02-28 发布日期:2017-02-28
通讯作者: 彭艳(1982—),女,副教授, 研究方向为无人艇导航和控制及其总体技术. E-mail: pengyan@shu.edu.cn
作者简介:彭艳(1982—),女,副教授, 研究方向为无人艇导航和控制及其总体技术. E-mail: pengyan@shu.edu.cn
基金资助:
国家自然科学基金资助项目(61403245); 上海市自然科学基金资助项目(13ZR1454300); 上海市科委能力建设资助项目(14500500400)

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. 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

摘要/Abstract

摘要：

海天线是海面环境图像所具有的重要特征之一, 海天线的检测对划分海空、海界区域以及目标检测有重要作用. 提出了一种结合结构森林快速边缘检测和概率Hough变换的海天线检测方法. 首先通过高斯低通滤波来减小海面浪纹、光照反射等局部纹理影响, 然后使用已完成训练的结构化随机森林为每个像素贴上边缘标签——二值化, 最后通过Hough变换原理拟合海天线. 实验结果表明, 该方法可以较好地忽略局部干扰边缘, 强化边界提取, 对复杂海天背景下的海天线检测具备鲁棒性和高准确性.

关键词: Hough变换, 边缘检测, 海天线检测, 结构化随机森林, 决策树

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

徐良玉1, 马录坤1, 谢燮1, 彭艳1, 彭艳青2, 崔建祥1. 基于结构森林边缘检测和Hough变换的海天线检测[J]. 上海大学学报(自然科学版), 2017, 23(1): 47-55.

XU Liangyu1, MA Lukun1, XIE Xie1, PENG Yan1, PENG Yanqing2, CUI Jianxiang1. Sea-sky line detection based on structured forests edge detection and Hough transform[J]. Journal of Shanghai University（Natural Science Edition）, 2017, 23(1): 47-55.

[1]	刘超, 安平, 赵冰, 闫吉辰, 张兆杨. 基于边缘的面向虚拟视绘制的深度编码算法[J]. 上海大学学报(自然科学版), 2014, 20(4): 450-457.
[2]	陈颖;陆亨立. 一种新的虹膜定位算法[J]. 上海大学学报(自然科学版), 2007, 13(2): 148-150 .

基于结构森林边缘检测和Hough变换的海天线检测

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

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