SEM Image Registration with CAD Data via Directionality Maps
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Solution Overview
Problem
Accurate registration of SEM images with CAD data is challenging due to differences in image modalities, complexity, and noise, making it difficult to generate a faithful simulated image for defect detection and classification in microelectronic devices.
Innovation Solution
The method involves generating directionality maps from both microscopic and CAD data, using gradient operators to compute directionality vectors, and comparing these maps to register the images, with post-processing steps to enhance correlation, including whitening, X-Y balancing, and corner balancing, and optionally combining with height maps for 3D shape registration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional image registration methods are used to align SEM images with CAD data, then the process can be automated, but the accuracy and reliability of registration deteriorates due to differences in image modalities, complexity, and noise
Solution Approach 1:
The patent introduces directionality maps as an intermediary representation that bridges SEM images and CAD data. Instead of directly aligning the two different image modalities, the system converts both into directionality maps that capture edge orientation information, enabling reliable registration through comparison of these intermediate representations.
Solution Approach 2:
The patent replaces traditional correlation-based registration methods with a directionality map comparison approach. By substituting the mechanical correlation operation with a directional vector comparison system, the method achieves more reliable registration that is robust to noise and modality differences.
2Manufacturing precision
If simulated images are generated from CAD data for registration, then alignment can be achieved, but the quality of simulated images deteriorates due to inability to faithfully reproduce imaging characteristics
Solution Approach 1:
The patent extracts the essential registration information from the complex image data by taking out directionality vectors that represent edge orientations. This extraction creates a simplified representation that captures the critical alignment features while discarding irrelevant imaging artifacts and noise, enabling precise registration without requiring high-fidelity simulated images.
Solution Approach 2:
The patent segments the image registration problem into separate components: generating directionality maps from SEM images, generating directionality maps from CAD data, and comparing these segmented representations. This segmentation allows each component to be optimized independently, improving overall registration precision without requiring perfect image simulation.
3Reliability
If directionality maps are generated and compared to register images, then registration reliability improves, but processing complexity increases due to additional computational steps
Solution Approach 1:
The patent performs preliminary action by pre-processing both SEM images and CAD data to generate directionality maps before the actual registration comparison. This preliminary transformation simplifies the subsequent registration process by converting complex image data into a standardized directional representation, making the overall system more reliable while managing computational complexity through structured processing stages.
Data Source
AI summary
A method for image processing includes providing a microscopic image of a structure fabricated on a substrate and computer-aided design (CAD) data used in fabricating the structure. The microscopic image is processed by a computer so as to generate a first directionality map, which includes, for a matrix of points in the microscopic image, respective directionality vectors corresponding to magnitudes and directions of edges at the points irrespective of a sign of the magnitudes. The CAD data are processed by the computer so as to produce a simulated image based on the CAD data and to generate a second directionality map based on the simulated image. The first and second directionality maps are compared by the computer so as to register the microscopic image with the CAD data.