Automated Template Image Evaluation for Charged Particle Beam Devices
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Solution Overview
Problem
Existing methods for maintaining a constant electron beam irradiation area in FIB-SEM imaging require experienced users to continuously monitor and correct the pattern matching process, making it burdensome for those unfamiliar with the technique.
Innovation Solution
An image evaluation method that acquires and evaluates a template image by moving it in orthogonal directions relative to a reference image, allowing for automated pattern matching process evaluation without continuous image acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user continuously monitors and performs pattern matching process to maintain constant electron beam irradiation area, then the imaging accuracy is improved, but the operational burden on the user increases significantly
Solution Approach 1:
The system automatically performs pattern matching and drift correction without requiring user intervention. The evaluation unit autonomously assesses template image appropriateness and the control unit automatically adjusts imaging parameters, enabling the system to self-correct and maintain imaging accuracy without continuous user monitoring
Solution Approach 2:
The evaluation unit continuously monitors the pattern matching process by comparing template images with actual images, providing feedback to the control unit. This feedback mechanism enables automatic adjustment of imaging parameters and template selection, resolving the contradiction by making the system self-regulating while maintaining high imaging accuracy
2Measurement precision
If the user determines template image appropriateness through continuous image acquisition and pattern matching, then the pattern matching accuracy is improved, but the time consumption and productivity decrease
Solution Approach 1:
The system performs preliminary evaluation of template image appropriateness before actual imaging using the evaluation unit. By pre-assessing template suitability through automated comparison and drift calculation, the system avoids time-consuming trial-and-error during the imaging process, thereby maintaining high pattern matching accuracy while improving overall processing efficiency
Solution Approach 2:
The evaluation unit periodically assesses template image appropriateness at predetermined intervals during imaging. This periodic evaluation ensures pattern matching accuracy is maintained without requiring continuous monitoring, as the system only performs evaluation when necessary, thus balancing accuracy with productivity
3Device complexity
If the system uses a fixed template image for pattern matching, then the device complexity is reduced, but the adaptability to different imaging conditions deteriorates
Solution Approach 1:
The system dynamically selects and switches between multiple template images based on imaging conditions and drift characteristics. The evaluation unit assesses which template is most appropriate for current conditions, and the control unit automatically switches templates as needed, enabling the system to adapt to varying imaging conditions while maintaining manageable complexity through automated decision-making
4Ease of operation
If the user is unfamiliar with pattern matching technique, then the ease of operation is improved for beginners, but the ability to accurately evaluate template images deteriorates
Solution Approach 1:
The evaluation unit autonomously performs template image assessment without requiring user expertise in pattern matching techniques. The system automatically compares templates, calculates drift, and determines appropriateness, enabling beginners to operate the system effectively while maintaining high evaluation accuracy through automated intelligent assessment
Data Source
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AI summary
An image evaluation method includes: a template image acquisition step (S10) that designates part of a reference image to acquire a template image; a first comparative image acquisition step (S101) that acquires a first comparative image in which the position of the template image is moved in a first direction by a first moving amount relative to the reference image; a first evaluation step (S103) that performs a pattern matching process on the template image and the first comparative image and evaluates the template image; a second comparative image acquisition step (S106) that acquires a second comparative image in which the position of the template image is moved in a second direction that is orthogonal to the first direction by a second moving amount relative to the reference image; and a second evaluation step (S108) that performs the pattern matching process on the template image and the second comparative image and evaluates the template image.