Charged Particle Beam Image Processing for Line Edge Roughness
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Solution Overview
Problem
Existing charged particle beam image processing devices only evaluate the periodicity of line edge groups, failing to assess continuity, which reduces measurement accuracy due to sparse intervals in the inspection region.
Innovation Solution
A charged particle beam image processing device that extracts line pattern edges, divides the inspection region into sections, measures line edge roughness, generates distribution data, calculates a theoretical curve, and determines the appropriateness of the inspection region by comparing data to the curve.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the inspection region is expanded to include more edges, then statistical reliability is improved, but the interval between edges becomes sparse and continuity is lost
Solution Approach 1:
By dividing the inspection region into multiple measurement regions, the system can include more edges across the expanded inspection region while maintaining adequate sampling density within each measurement region. This ensures both statistical reliability through increased sample size and continuity through proper spacing within sections.
Solution Approach 2:
The system adjusts the determination value based on the relationship between measured and theoretical line edge roughness, dynamically optimizing the inspection region parameters to maintain appropriate edge intervals while expanding the overall inspection area for better statistical reliability.
Data Source
AI summary
To provide a charged particle beam image processing device in which a proper inspection region for an observation image that includes an edge of a line pattern can be set.A charged particle beam image processing device performs image processing on an observation image generated by a charged particle beam apparatus, the charged particle beam image processing device includes: an extraction unit configured to extract an edge of a line pattern from an inspection region of the observation image; a division unit configured to divide the inspection region into sections each having a plurality of measurement points; a measurement unit configured to measure a line edge roughness in each of the sections and generate distribution data of the line edge roughness in each section; a calculation unit configured to calculate a line edge roughness in the entire inspection region and calculate a theoretical curve of the line edge roughness in each section; and a determination unit configured to determine whether the inspection region is proper based on a comparison between the distribution data and the theoretical curve.