摘要
基于图像的月球表面障碍自主检测技术是实现探测器在月球表面安全着陆的关键。本文主要研究了基于被动图像的月球表面障碍物之一的岩石的检测技术。首先将最大二维熵阈值分割用于岩石阴影的检测;其次将岩石轮廓线提取技术与阴影检测结果结合以获取精确的拟合椭圆中心点;最后,利用椭圆拟合岩石所在的区域范围。实验表明:相较于传统的仅基于阴影的算法,本文提出的岩石障碍检测算法能更好地拟合出岩石所在区域范围。
For autonomous landing of lunar probe, to develop autonomous landing and hazard avoidance technology is very necessary and the key of this technology is hazard detection. The focus of this paper was to present an algorithm for autonomous rock (one kind of hazard on moon surface) detection based on passive images. The paper could be divided into three parts. Firstly, Maximum 2D Entropy Thresholding was employed for detection of rock shadow. Secondly, the result of shadow detection was combined with rock contour extraction for more precise center point of ellipse which describes rock area. Finally, the parameters of this ellipse were computed and rock areas were confirmed. Experimental studies demonstrate that the algorithm of rock detection can describe scope of rock area more successfully than only shadow-based method.
出处
《光电工程》
CAS
CSCD
北大核心
2009年第1期82-87,共6页
Opto-Electronic Engineering
基金
江苏省研究生创新基金(CX07B_113z)
南京航空航天大学博士创新基金(BCXJ07-06)
关键词
被动图像
岩石检测
阴影检测
二维最大熵
passive image
rock detection
shadow detection
Maximum 2D Entropy