Surface Analyzer ROI Specification via Image Superposition
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Solution Overview
Problem
Current surface analyzers, such as scanning probe microscopes, face inefficiencies in specifying regions of interest for measurements based on two-dimensional distribution data of physical quantities other than altitude, as users must visually compare images, leading to cumbersome and error-prone processes.
Innovation Solution
A surface analyzer with display processors to create and superpose two-dimensional distribution images of various physical quantities on a range-indicating image, allowing users to easily select and specify regions of interest, including features like image lists, selectors, and range specifiers for precise measurement control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a broad-area image showing surface shape and a magnified observation image showing a certain physical quantity are simultaneously displayed, then users can grasp positional relationships, but it is difficult to know which portion on the broad-area image corresponds to the magnified observation image
Solution Approach 1:
The patent applies color coding to different image types (altitude image vs. physical quantity image) displayed on the screen. By assigning distinct colors or color schemes to represent different measurement types, users can immediately distinguish which portions correspond to each other across the broad-area and magnified views, eliminating confusion about image correspondence.
Solution Approach 2:
The patent creates a composite image that copies and overlays information from both the broad-area altitude image and the magnified physical quantity image into a single integrated display. This composite representation allows users to see both views simultaneously with clear spatial correspondence, eliminating the need to mentally match separate images.
2Measurement precision
If users specify region of interest by visually comparing frame on broad-area image and previously taken image, then region can be selected, but the task is cumbersome and may cause error in judgment
Solution Approach 1:
The patent implements automatic feedback mechanisms where the system provides visual cues (such as highlighted boundaries, color-coded regions, or automated overlays) that immediately show users which area corresponds to their selection criteria. This feedback loop eliminates the need for manual visual comparison and reduces selection errors.
Solution Approach 2:
The patent enables the system to automatically identify and highlight the region of interest based on user-defined criteria without requiring manual visual comparison. The system performs the matching and selection task itself, saving user time and reducing errors while maintaining precision.
3Adaptability or versatility
If multiple magnified observation images are taken for different physical quantities, then comprehensive data is obtained, but it is very time-consuming to observe distribution on desired portion while grasping positional relationships
Solution Approach 1:
The patent merges multiple magnified observation images showing different physical quantities into a single composite display that maintains spatial correspondence with the broad-area view. By combining these images with clear visual indicators of their respective locations, users can efficiently observe distributions across multiple physical quantities without the time-consuming process of switching between separate images.
Data Source
AI summary
A technique for allowing users to efficiently specify a region of interest (ROI) on a sample for a certain physical quantity (e.g. phase) other than the altitude is provided. A range-indicating image showing a range that can be observed on a sample is displayed on a navigation window in a sample observation display screen. An ROI-indicating frame for specifying a magnified observation range is superposed on the range-indicating image. A list of thumbnails of previously taken magnified images for the same sample is displayed on an image history display window. When an observer selects any image from this list, the thumbnail of the selected image is mapped onto the range-indicating image. With reference to this image, the observer can change the position, size and/or angle of the ROI-indicating frame by a mouse operation. In response to this operation, a magnified image of the sample within the new ROI is acquired.