# Histogram-based Auto Segmentation: A Novel Approach to Segmenting Integrated Circuit Structures from SEM Images

arXiv: https://arxiv.org/abs/2004.13874 · HTML: https://mlsanity.com/paper/2004.13874/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Apr 2020.

## Built on by (most cited first, 2 of 2)

- [Unsupervised Domain Adaptation with Histogram-gated Image Translation for Delayered IC Image Analysis](https://mlsanity.com/paper/2209.13479/) (2022)
- [Automatic Error Detection in Integrated Circuits Image Segmentation: A Data-driven Approach](https://mlsanity.com/paper/2211.03927/) (2022)

## Abstract (arXiv)

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.