An Edge Detection Algorithm for SEM Images of Multilayer Thin Films
Wei Sun, Fang Duan, Jianpeng Zhu, Minglai Yang, Ying Wang
Abstract
In processing multilayer thin film materials, scanning electron microscopy (SEM) is commonly employed for observation. In images of SEM, backscattered electron (BSE) images is particularly suitable for distinguishing different components and layers of the films. However, at high magnification levels, BSE images often have blurriness and noise, leading to low edge sharpness. This study proposes a method for improving the integrity and accuracy of the edges. First, we segment the image into different contrast regions using the masking algorithm. Second, we enhance the images in separate regions by the enhancement algorithm. Finally, we combine the regions by logical operations. In instantiation, we implement our approach on SEM-BSE images. It was found that the edges are significantly sharpened through the assessment of the edge evaluation algorithm.