Mask Pattern Evaluation Using Image Moments
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Solution Overview
Problem
Current methods for evaluating mask patterns in micro-electronic device manufacturing are inefficient due to the high computational requirements and complexity of image processing, especially when dealing with critical dimensions below 65 nm, where systematic variations consume a significant portion of the error budget.
Innovation Solution
A method and system that utilize multiple moments to represent mask patterns, allowing for efficient processing and comparison by determining moment differences and using a mapping function to calculate pattern differences, reducing the information size and enabling faster evaluation and contour representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex image processing schemes with large number of pixels are used for CD measurements, then measurement precision is improved, but processing time and computational complexity increase significantly
Solution Approach 1:
The patent extracts only the essential shape information from the full image by calculating image moments (M00, M10, M01, M20, M02, M11). These moments capture the critical dimensional and shape characteristics needed for CD measurement without requiring processing of every pixel in the image, thus reducing measurement time while maintaining precision
Solution Approach 2:
The patent transforms the image representation from pixel-domain to moment-domain by computing statistical moments. This parameter transformation reduces the data dimensionality from thousands of pixels to just six moment values, enabling fast comparison and CD calculation while preserving the essential shape information needed for accurate measurements
2Manufacturing precision
If detailed pixel information is processed for pattern evaluation, then evaluation accuracy is improved, but computational load and system complexity increase
Solution Approach 1:
The patent extracts only the necessary shape characteristics through moment calculation, obtaining M00 (area), M10 and M01 (centroid position), M20 and M02 (second moments for shape). This extraction provides sufficient information for accurate pattern evaluation without the complexity of processing complete pixel arrays
Solution Approach 2:
The patent segments the complex image processing task into distinct moment calculation components (M00, M10, M01, M20, M02, M11), each capturing specific shape attributes. This segmentation simplifies the overall processing complexity while maintaining comprehensive shape information for accurate evaluation
3Manufacturing precision
If systematic variations in critical dimensions are measured with high precision, then CD control is improved, but the error budget is consumed by measurement and processing requirements
Solution Approach 1:
The patent changes the measurement parameters from full-image pixel data to compact moment representations. This parameter transformation reduces the information overhead and processing burden, freeing up error budget while maintaining the precision needed to detect and control systematic CD variations across the mask
Data Source
AI summary
A method, system and a computer program product for evaluating an evaluated pattern of a mask, the method includes: receiving multiple moments that represent an image of the evaluated pattern; wherein a size of information required for representing the multiple moments is substantially smaller than a size of pixel information that form the image of the evaluated pattern; and processing the multiple moments in order to determine at least one shape parameter of the evaluated pattern.