基于SEM图像的自动对焦技术

Auto-Focusing Technology Based on SEM Images

针对扫描电子显微镜(SEM)自动对焦技术对噪声敏感,计算量大,从而影响SEM自动对焦的准确性和实时性,提出一种基于SEM图像的自动对焦技术。该技术采用基于拉普拉斯高斯算子和局部方差相结合的对焦评价函数FGLOG描述SEM的对焦状态;采用显著区提取和凸包法相结合的方法,自动提取SEM图像感兴趣区域(ROI)。实验结果表明,与5种典型的对焦评价函数对比,提出的对焦评价函数FGLOG可以有效抑制噪声。在较少幅的帧平均情况下,仍然可以正常工作,可以提高自动对焦效率。针对不同的IC图形,采用ROI选取技术可以改善对焦评价函数曲线的灵敏度。尤其针对IC孤立线条,灵敏度得到有效提高。

The scanning electron microscope（SEM）auto-focusing technique is sensitive to noise and has amount of calculation,which will affect the accuracy and real-time performance.An autofocusing technique based on SEM images was proposed.The focusing evaluation function（FGLOG）based on Laplace of Gaussian and local variance was used to describe the SEM focusing state,and the automatic extraction method based on salient region and convex hull was used to select the region of interest（ROI）of SEM images.The experimental result show that the proposed focusing evaluation function（FGLOG）has better anti-noise performance than those of five typical focusing evaluation functions.It can work with SEM images averaged out with less frames,and the autofocusing can be improved.By using the proposed ROI extraction technology,the sensitivity of the focusing evaluation function can be improved for different IC patterns.Especially for the IC isolated lines,the sensitivity can be improved effectively.