光纤倒像器生产过程中容易产生鸡丝、斑点等缺陷, 检测时如何自动识别一直是研究重点。提出一种阈值分割方法, 对检测时采集的光纤倒像器图像先平滑滤波得到平均亮度图像, 再用采集的原始图像减去平均亮度图像, 对二者的差图像设定阈值进行二值化处理, 实现缺陷的自动分割。实验中使用典型的鸡丝、斑点缺陷图像, 验证了上述算法的有效性, 表明该方法能满足光纤倒像器的检测需求。

In the production process of fiber image inverters, it is easy to produce chicken defect, spot and other defects, and how to automatically identify the defects has been the focus of research. A threshold segmentation method is proposed which smoothes the obtained filter image to get an average brightness image. And the average image is subtracted from the original image to get a difference image. The difference image is binarized by a threshold to realize the automatic segmentation of the defect. In the experiment, the effectiveness of the above algorithm is verified by using the typical image of the chicken and the spot defects, which indicates that the method can meet the requirements of fiber image inverters.