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.
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.
出处
《上海大学学报（自然科学版）》
CAS
CSCD
北大核心
2017年第1期47-55,共9页
Journal of Shanghai University:Natural Science Edition
基金
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)
