【摘要】 针对深空探测任务中行星表面特征检测与识别问题,提出了一种新的行星表面非规则陨石坑检测与识别方法。首先采用基于背景的Hopfield网络实现陨石坑边缘的提取,在对陨石坑边缘多种约束进行分析的基础上,提出了伪边缘剔除方法,并结合线性抗差估计理论与最小误差中值椭圆拟合方法,实现了对非规则陨石坑,特别是重叠及不完整陨石坑的检测及特征参数的提取。通过对行星表面光学图像的数学仿真验证了该方法能够对复杂背景下的非规则陨石坑进行有效的检测与识别。更多还原

【Abstract】 The paper focuses on the feature detection and recognition on planetary surface in the deep space exploration mission.A novel detection and recognition method for irregular craters,especially overlapped and incomplete craters on planetary surface is proposed.First,extraction of candidate crater edge is performed by using the Contextual-based Hopfield neural network.Furthermore,pseudo-edges which do not satisfy the constraints are removed by analyzing multi constraints for real crater edges.Finally,real edges containing the feature of the crater are detected by using the least median square ellipse fitting method combined with a robust least square method.Meanwhile the physical parameters are determined.Mathematical simulations demonstrate the performance of the proposed method for detection and recognition of irregular craters in complex background.更多还原