Fully automated or semi-automated scanning electron microscopes (SEM) are now commonly used in semiconductor production and other forms of manufacturing. Testing and proving that the instrument is performing at a satisfactory level of sharpness is an important aspect of quality control. The application of Fourier analysis techniques to the analysis of SEM images is a useful methodology for sharpness measurement. In this paper, a statistical measure known as the multivariate kurtosis is proposed as an additional useful measure of the sharpness of SEM images. Kurtosis is designed to be a measure of the degree of departure of a probability distribution. For selected SEM images, the two-dimensional spatial Fourier transforms were computed. Then the bivariete kurtosis of this Fourier transform was calculated as though it were a probability distribution, Kurtosis has the distinct advantage that it is a parametric (I.e., a dimensionless) measure and is sensitive to the presence of the high spatial frequencies necessary for acceptable levels of image sharpness. The applications of this method to SEM metrology will be dissussed.
Pub Type: Journals
Fourier transform, image analysis, kurtosis, metrology, scanning electron microscope