基于阴影特征的月面凹障碍自动识别检测方法

Automatic Recognition and Detection of Lunar Concave Obstacles Based on Shadow Feature

基于月面凹障碍在光照下存在阴影和高亮区一一对应的特征,提出一种月面凹障碍自动识别检测方法。运用自适应双阈值分割法将凹障碍的阴影区和高亮区从背景中自动分割出来,并聚类出每个阴影区和高亮区具体的位置;引入先验光照信息,利用光照方向对阴影和高亮区精确匹配,完成对单个凹障碍粗提取;遍历所有包含单个凹障碍的原始图像子图像序列,进行边缘检测和参数拟合,解决了同时处理多个障碍的干扰影响,能够有效识别检测所有凹障碍的位置和范围。

The widespread impact craters and other concave obstacles on the lunar surface are the key factors threatening the safe landing and roving of the lunar rover.Once trapped,it will bring risks of tilt,landslide,and even rollover to the lunar rover.Therefore,the effective recognition and detection of lunar concave obstacles are conductive to obstacle avoidance,and provide necessary information reference for the safe landing and roving of the lunar rover.Based on the concave obstacles’feature that there is a one-to-one matching between the shadows and the highlights in the sun,an automatic recognition and detection method for the lunar concave obstacles is proposed.The adaptive dual threshold method is used to automatically separate the shadows and the highlights of the concave obstacles from the background.Each shadow and highlight are clustered the specific position and one-toone matched using the sunlight direction with the prior forecast information involved.Then the rough extraction of every single concave obstacle are obtained.Finally the original sub-images sequence containing every single concave obstacle is traversed for edge detection and ellipse fitting,which can avoid mutual interference of multiple obstacles and effectively detect the locations and ranges of all concave obstacles.