Sharpness Map Surface Profiling Without Sub-Pixel Registration
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Solution Overview
Problem
Existing optical metrology methods for measuring workpiece surfaces face challenges in accurately and efficiently determining depth information and reconstructing 3-D profiles due to image registration requirements and distortion near edges, leading to increased calculation time and reduced accuracy.
Innovation Solution
A method involving capturing images with defined 6-DOF poses and focal plane positions, generating sharpness maps, transforming these maps into a global reference system, and using sharpness clouds to determine surface profiles without sub-pixel registration, allowing for robust and accurate 3-D reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sub-pixel registration is performed on laterally displaced image stacks, then depth information can be extracted, but calculation time increases and accuracy is reduced due to distortion near edges
Solution Approach 1:
The patent applies preliminary action by capturing images along the optical axis (Z-direction) at different focal planes before any processing occurs. This approach establishes proper focus information upfront, eliminating the need for complex post-capture registration operations. By acquiring data in the optimal sequence and orientation from the beginning, the method avoids time-consuming sub-pixel registration and edge distortion correction that would be required if images were captured laterally
Solution Approach 2:
The patent inverts the conventional approach by instead of moving the optical sensor laterally (XY-plane) to capture multiple regions and then registering them, it moves the focal plane along the optical axis (Z-direction) to capture depth information directly. This inversion transforms the problem from a 2D registration challenge into a 1D focus-based depth extraction, dramatically reducing calculation time and avoiding edge distortion issues
2Area of stationary object
If images are captured with lateral displacement of optical sensor, then larger surface region can be measured, but sub-pixel registration is required increasing device complexity and calculation time
Solution Approach 1:
The patent applies dimensionality change by transitioning from lateral (XY-plane) image capture to axial (Z-direction) focal plane capture. Instead of displacing the sensor laterally to expand the measured area and then performing complex 2D registration, the method utilizes the Z-direction focal stacking capability to capture depth information for each point. This dimensional shift transforms a complex multi-step registration problem into a simpler focus-based depth extraction process
Solution Approach 2:
The patent extracts only the essential depth information directly from focal variations in the captured images, eliminating the need to perform full image registration. By focusing on the Z-direction focal plane positions and extracting depth data from sharpness variations, the method separates the depth measurement function from the lateral positioning function, thereby reducing processing complexity while maintaining measurement capability
3Measurement precision
If conventional shape from focus method is used with laterally displaced images, then 3-D information can be reconstructed, but edge regions show distortion reducing measurement precision
Solution Approach 1:
The patent applies preliminary action by capturing properly focused images at multiple Z-direction focal planes before processing. This ensures that edge regions are captured at their optimal focus positions in each image, preserving edge information integrity from the outset. The preliminary capture of depth-coded focal information prevents the edge distortion that occurs when attempting to register laterally displaced images post-capture
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
Enables rapid and precise 3-D surface reconstruction by directly evaluating sharpness information at acquisition points, reducing calculation time and enhancing edge detection, resulting in improved accuracy and robustness.
Implementation Method 1
The optical system of the optical sensor has a focal plane, which is a plane of greatest sharpness. If an object point located on the surface of the workpiece is moved toward the focal plane, then the image representation of the object point becomes sharper. If the object point is moved away from the focal plane, then the image representation of the object point becomes less sharp.
Data Source
AI summary
A method includes capturing images of a surface of a workpiece using an optical sensor. Each image respectively images a region of the surface. Each image is assigned a defined 6-DOF pose of the optical sensor relative to the workpiece and a defined focal plane position of the optical sensor. The captured images form an image stack. The method includes determining a sharpness value for each picture element of each image of the image stack to generate a sharpness map for each image. The sharpness maps of the images form a sharpness map stack. The method includes transforming the sharpness maps of the sharpness map stack into a defined reference system based on the respective assigned 6-DOF pose and focal plane position of the optical sensor in order to generate a sharpness cloud. The method includes generating a surface profile of the workpiece based on the sharpness cloud.