保偏光子晶体光纤图像特征孔中心提取算法

Photonic Hole Center Extraction Algorithm for Polarization-Maintaining Photonic Crystal Fibers

保偏光子晶体光纤快慢轴的检测是保偏光子晶体光纤应用的关键技术。针对保偏光子晶体光纤端面空气孔数量多、尺寸存在差异及噪声和伪边缘干扰圆心定位精度的问题,提出一种双峰均值二值化法粗定位和径向扫描三点法精定位相结合的方法。采用双峰均值二值化法实现空气孔重心的粗定位;利用大空气孔定方位,选取两个具有结构对称的空气孔区域,去除粗大误差点,径向扫描法确定边缘三点进行圆心精定位,并利用半径阈值减小误差。实验结果表明,该方法能有效分割光纤端面图像,圆心偏差小于0.2个像素,为光纤定轴打下必要的理论基础。

Detection of the fast and slow axes is regarded as a key technology in applications of the polarization-maintaining photonic crystal fiber. Aiming at such problems as large amount of air holes, noise and pseudo-edges, a positioning method which combines coarse positioning by bimodal mean binarization method and fine positioning by radial scanning three-point precision method was proposed. The former method was used to realize rough positioning of the center of gravity of air holes. Then, it uses the big air hole to orientate, selects two air hole areas with symmetric structure, removes the coarse error points, determines the three edge points to accurately locate the center of the circle, and uses the radius threshold to reduce the error. Experimental results show that the proposed method can segment the fiber surface image effectively, and the center error is less than 0.2 pixels.