SPM Image Edge Dilation for Accurate Surface Correction
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Solution Overview
Problem
Existing scanning probe microscopes struggle to accurately detect edges of structures, leading to inaccurate correction of SPM images and an unclear representation of the sample's surface state.
Innovation Solution
A data processing method that involves extracting edge pixels, dilating the edges, and generating data to determine regions corresponding to substrates and structures, followed by inclination correction to provide accurate surface representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If edge detection is performed using conventional methods on SPM image data, then processing can be completed, but the edge of the structure cannot be detected accurately
Solution Approach 1:
The patent applies preliminary actions by performing dilation on the edge pixels before using them for image correction. The dilation process expands the edge regions to ensure that the entire structure is properly encompassed, preventing incomplete detection. This preliminary expansion of edge data ensures that subsequent correction processes work with comprehensive boundary information, resolving the accuracy issue in edge detection and image correction.
2Productivity
If three points from substrate region are used for height correction, then correction processing can be performed, but the surface state cannot be provided accurately when edge detection fails
Solution Approach 1:
The patent implements feedback by using the dilated edge information to accurately define the substrate region boundaries. The corrected height information from the substrate region is then fed back to improve the overall image correction process. This feedback mechanism ensures that the three points selected for height correction are reliably from the substrate region, and the correction results accurately represent the true surface state, resolving the precision issue in surface state representation.
3Loss of time
If conventional edge detection is used, then processing speed is maintained, but the region corresponding to substrate cannot be determined accurately
Solution Approach 1:
The patent applies preliminary action by performing dilation on edge pixels before determining the substrate region. This dilation process pre-expands the edge boundaries to ensure complete coverage of the structure, making the subsequent substrate region identification more accurate. The preliminary expansion prevents under-sampling of edge regions and ensures that the substrate region is correctly identified without requiring additional processing iterations, thus maintaining processing speed while improving accuracy.
Data Source
AI summary
A computer (132) obtains image data (step S10), extracts from the image data as an edge pixel a pixel satisfying a condition that a result of comparing with an adjacent pixel is an edge (step S12), and generates first data by dilating an edge including the edge pixel (step S14). Then, the computer (132) uses the first data to generate second data that determines a region in a sample corresponding to a substrate (step S22).