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SEM images provide valuable information about patterning capability. Geometrical properties such as Critical Dimension (CD) can be extracted from them and are used to calibrate OPC models, thus making OPC more robust and reliable. However, there is currently a shortage of appropriate metrology tools to inspect complex two-dimensional patterns in the same way as one would work with simple one-dimensional patterns. In this article we present a full framework for the analysis of SEM images. It has been proven to be fast, reliable and robust for every type of structure, and particularly for two-dimensional structures. To achieve this result, several innovative solutions have been developed and will be presented in the following pages. Firstly, we will present a new noise filter which is used to reduce noise on SEM images, followed by an efficient topography identifier, and finally we will describe the use of a topological skeleton as a measurement tool that can extend CD measurements on all kinds of patterns. © 2017 SPIE.

Edge extraction, Noise reduction, SEM images, Skeleton

Inspection, Musculoskeletal system, Noise abatement, Photolithography, Units of measurement, Edge extraction, Geometrical property, One-dimensional patterns, SEM image, Skeleton, Topological skeletons, Two-dimensional patterns, Two-dimensional structures, Process control