锥套定位的高精度点圆特征提取算法

High-precision point-circle feature extraction algorithmfor refueling drogue positioning

光学标记辅助加油锥套识别定位系统中,快速高精度提取光学标记质心坐标是锥套定位的重要基础。实际应用场景下,工作距离越远,光学标记点特征的成像越弱;且复杂的背景干扰使得质心提取的准确性大大降低。通过分析光学标记点、圆特征的成像特性,结合锥套结构特点,对光学标记圆特征进行提取,精确分割锥套有效特征区域以代替全局搜索,剔除大量背景干扰;进而提出了一种由类FAST阈值粗定位法与二维高斯残差重心拟合法相结合的二级高效点特征质心提取算法,通过设置亮度阈值快速识别光斑特征并获取粗略位置,在此基础上精确框选光斑像素分布邻域,拟合计算提取高精度亚像素质心坐标。实验表明,本文算法满足实时提取要求,与其他经典算法相比,本文算法在保持较高精度的同时,稳定性也能达到较高水平。

In the optical marker-assisted drogue positioning system, the rapid and high-precision extraction of the optical mark is an important foundation for the positioning of the drogue. In practical application scenarios, the longer the working distance, the weaker the imaging of the point features. And the complex background interference greatly reduces the accuracy of centroid extraction. By analyzing the characteristics of optical marking points and circular features, combined with the structural characteristics of the drogue, the circular feature of the optical marking is extracted so that the effective feature area, which is used to replace the global search, can be segmented to eliminate the background interference accurately. Furthermore, this paper mainly proposes a two-level high-efficiency point feature centroid extraction algorithm that combines the FAST-like threshold coarse localization method and the two-dimensional Gaussian residual centroid fitting method. The method identifies the spot features and obtains the rough position quickly by setting the brightness threshold. On this basis, the sub-pixel centroid coordinates are extracted by fitting calculation in the pixel distribution neighborhood of the spot. Experiments results show that the proposed algorithm meets the real-time extraction requirements. Compared with other classical algorithms, the algorithm can maintain a high accuracy and achieve a high level of stability.