In the hardware assurance community, Reverse Engineering (RE) is considered a key tool and asset in ensuring the security and reliability of Integrated Circuits (IC). However, with the introduction of advanced node technologies, the application of RE to ICs is turning into a daunting task. This is amplified by the challenges introduced by the imaging modalities such as the Scanning Electron Microscope (SEM) used in acquiring images of ICs. One such challenge is the lack of understanding of the influence of noise in the imaging modality along with its detrimental effect on the quality of images and the overall time frame required for imaging the IC. In this paper, we characterize some aspects of the noise in the image along with its primary source. Furthermore, we use this understanding to propose a novel texture-based segmentation algorithm for SEM images called LASRE. The proposed approach is unsupervised, model-free, robust to the presence of noise and can be applied to all layers of the IC with consistent results. Finally, the results from a comparison study is reported, and the issues associated with the approach are discussed in detail. The approach consistently achieved over 86% accuracy in segmenting various layers in the IC.