Histogram-based Auto Segmentation: A Novel Approach to Segmenting Integrated Circuit Structures from SEM Images
This addresses a domain-specific need in Reverse Engineering and Hardware Assurance for effective segmentation from low-quality SEM images, but it is incremental as it builds on existing techniques.
The paper tackles the problem of segmenting Integrated Circuit structures from SEM images by introducing an unsupervised, parameter-free algorithm that does not require prior noise or feature information, and reports results on various IC structures and layers.
In the Reverse Engineering and Hardware Assurance domain, a majority of the data acquisition is done through electron microscopy techniques such as Scanning Electron Microscopy (SEM). However, unlike its counterparts in optical imaging, only a limited number of techniques are available to enhance and extract information from the raw SEM images. In this paper, we introduce an algorithm to segment out Integrated Circuit (IC) structures from the SEM image. Unlike existing algorithms discussed in this paper, this algorithm is unsupervised, parameter-free and does not require prior information on the noise model or features in the target image making it effective in low quality image acquisition scenarios as well. Furthermore, the results from the application of the algorithm on various structures and layers in the IC are reported and discussed.