Particle Beam Markings for Reliable Image Stitching
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Solution Overview
Problem
Existing particle beam devices face challenges in generating composite images of large samples due to the lack of distinct features in the common regions of sub-images, leading to uncertain alignment and insufficient stitching outcomes, especially when features are repetitive or extend along a common straight line, which hinders the generation of unique relative positions of sub-images.
Innovation Solution
The method involves generating distinctive features, such as markings, within the object's surface using a particle beam, which serve as alignment markers for sub-image stitching. These markings are calculated to be positioned in specific locations within the sub-images, allowing for precise alignment and overlap of sub-images to create a composite image, even in areas with no or unusable features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image stitching is performed using existing distinct features in the common region, then alignment can be achieved, but the method fails when no distinct features or only repetitive features are present
Solution Approach 1:
The patent applies preliminary action by generating markings at predetermined positions before image stitching is performed. These markings are created in advance on the sample surface at known coordinate positions, ensuring that distinct alignment features exist in the common region between sub-images even when the original sample lacks such features. This pre-preparation of alignment markers resolves the contradiction by guaranteeing reliable alignment regardless of the sample's natural feature content.
Solution Approach 2:
The patent introduces markings as intermediary elements that mediate between the sample surface and the image stitching process. These artificial markers serve as a bridge, providing distinct, identifiable features in the common region that enable reliable alignment. The markings act as an intermediary layer that decouples the alignment reliability from the presence of natural sample features, allowing consistent stitching performance across diverse sample types.
2Manufacturing precision
If markings are generated on the object surface to enable alignment, then stitching accuracy improves, but the object is modified
Solution Approach 1:
The patent applies local quality by creating markings only at specific, localized positions on the sample surface rather than uniformly across the entire sample. The markings are generated at predetermined coordinate positions that are strategically selected to be in the common region between sub-images. This localized approach provides sufficient alignment information while minimizing modification to the overall sample, thus balancing stitching accuracy with sample preservation.
Solution Approach 2:
The patent implements discarding and recovering by temporarily introducing markings for the alignment process and then removing them after stitching is complete. The markings serve their purpose during the alignment and stitching phase, and subsequent removal restores the sample to its original state. This approach allows high stitching accuracy during processing while eliminating the harmful modification effect in the final result.
3Area of stationary object
If multiple sub-images are stitched together to create large composite images, then coverage area increases, but alignment uncertainty increases when features are repetitive or extend along a common straight line
Solution Approach 1:
The patent applies preliminary action by pre-calculating and pre-positioning markings at specific coordinate locations before image acquisition. The marking positions are determined in advance based on the planned tiling arrangement, ensuring that each sub-image contains distinct, identifiable markers in its common regions. This pre-planning eliminates alignment uncertainty even when stitching multiple sub-images together, maintaining high precision across large composite images regardless of the sample's natural feature pattern.
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 reliable and automatic image stitching with reduced computation time, independent of surface features, ensuring accurate alignment and generation of composite images without modifying the object and allowing for the removal of markings post-processing.
Implementation Method 1
an electron beam device, in particular a scanning electron microscope (also known as SEM). In an SEM, an electron beam (hereinafter also called primary electron beam) is generated using a beam generator
Implementation Method 2
ions are generated which are used for processing a sample
Implementation Method 3
focused by a beam guiding system, in particular an objective lens, onto a sample to be analyzed
Implementation Method 4
electrons are emitted by the sample to be analyzed (so-called secondary electrons)
Implementation Method 5
electrons of the primary electron beam are backscattered at the sample to be analyzed (so-called backscattered electrons)
Implementation Method 6
interaction radiation arise(s) as a consequence of the interaction
Data Source
AI summary
The system described herein relates to a method for generating a composite image of an object using, for example, a particle beam device such as an electron beam device and/or an ion beam device. A composite image is generated by relatively arranging a first sub image to a second sub image such that the first sub image overlaps the second sub image in the entire common region, a calculated first image position of a first marking in the first sub image is arranged on the first image position of the first marking in the second sub image, and a calculated second image position of a second marking in the first sub image is arranged on the second image position of the second marking in the second sub image.