Contour Extraction via Backscattered Electron Dictionary
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Solution Overview
Problem
Existing contour extraction methods from electron beam images face challenges in accurately extracting contours due to the susceptibility of secondary electron images to charging effects, leading to blurred images and reduced accuracy.
Innovation Solution
A contour extraction method that creates a dictionary associating secondary electron images with backscattered electron images from common portions, allowing for the calculation of contour likelihoods in new images and determining the contour route that maximizes the total likelihood, thereby enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If secondary electron images are used for contour extraction, then the image provides detailed surface information, but charging effects cause image blur and reduce extraction accuracy
Solution Approach 1:
The patent uses backscattered electron images as an intermediary to transfer contour information from the charging-prone secondary electron images. The BSE images serve as a stable reference that is not affected by charging, allowing accurate contour extraction while maintaining the benefits of SE image detail
Solution Approach 2:
The patent creates a dictionary that copies contour information from BSE images to SE images. By learning the correspondence between BSE and SE images during a teaching period, the system can accurately extract contours from SE images even when they are blurred by charging effects
2Measurement precision
If conventional contour extraction methods are used from secondary electron images, then the process is simple and fast, but the position accuracy is low due to image blur
Solution Approach 1:
The patent performs preliminary actions by acquiring both BSE and SE images during a teaching period before actual contour extraction. This pre-processing step creates a dictionary that associates BSE contour information with SE image data, enabling high-accuracy extraction without increasing the complexity of the main extraction process
Solution Approach 2:
The patent changes the approach from directly extracting contours from SE images to using a probabilistic model that references BSE images. By calculating likelihoods based on the dictionary and using dynamic programming to find the maximum likelihood path, the system achieves higher accuracy while managing complexity through algorithmic optimization
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables precise contour extraction with improved accuracy, overcoming the limitations of secondary electron image susceptibility to charging and achieving higher position accuracy compared to conventional methods.
Implementation Method 1
an image obtained using an electron beam
Implementation Method 2
a secondary electron image obtained from a portion common to the backscattered electron image
Data Source
AI summary
According to one embodiment, a contour extraction method for extracting a contour of a target object from an image obtained using an electron beam includes: extracting the contour of the target object from a backscattered electron image; creating a dictionary for associating a secondary electron image obtained from a portion common to the backscattered electron image with the contour; calculating a likelihood of the contour of the target object in a plurality of positions of a newly obtained secondary electron image by referencing the dictionary regarding the newly obtained secondary electron image; and setting a route along which a total sum of the likelihood is maximized out of the plurality of positions as the contour of the target object.