包覆层表面缺陷的检测是保证发动机装药质量的重要手段。针对采集的包覆层表面缺陷图像,利用数学形态学的顶帽与低帽变换相结合的方法进行了缺陷特征增强,采用高低阈值的方法实现了缺陷图像的分割,得到了二值化图像,并通过中心半径标定,得出了有效检测区域,计算出了缺陷的大小和位置,检测结果表明,该方法的位置检测精度小于0.4mm,检测分辨率可达到Δ0.5mm,尺寸检测精度小于0.2mm。

The surface defect inspection of coating is an important means to ensure the quality of solid rocket motor charge. As for surface defect images of coating, the combination of top-hat and bottom-hat of mathematical morphology was used to enhance the defect characteristic. The segmentation of defect image was realized by high-low threshold and binary image was obtained. The valid inspection region was achieved by centre-radius calibration, and the size and location of defect were calculated. The results show that the precision of location is less than 0.4 mm, the resolution can reach 0.5 mm, and the precision of size is less than 0.2 mm.