Displacement Measurement Apparatus Using Spatial Frequency Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional displacement measurement apparatuses face errors beyond optical magnification distortion, particularly when low-frequency components dominate the spatial frequency component of measurement target images, leading to increased measurement errors due to surface roughness, distance changes, and motion-related blurring or shaking.
Innovation Solution
A measurement apparatus that calculates measurement values using a cross-correlation function of two images and corrects these values based on the spatial frequency component configuration, employing a double-sided telecentric optical system and sub-pixel estimation with quadratic or linear function fitting to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional displacement measurement methods are used, then measurement can be performed, but measurement precision deteriorates due to errors from low-frequency spatial components and surface roughness
Solution Approach 1:
The patent changes the parameter of spatial frequency component selection by calculating the spatial frequency spectrum of the measurement target image and selecting only the high-frequency component range for correlation calculation. This parameter change filters out low-frequency components that cause measurement errors due to surface roughness and lighting conditions, thereby improving measurement precision and reliability simultaneously
Solution Approach 2:
The patent extracts only the high-frequency spatial components from the measurement target image by calculating the spatial frequency spectrum and selecting a specific frequency range. This extraction removes the harmful low-frequency components that cause measurement errors, allowing accurate displacement measurement even on surfaces with roughness or under varying lighting conditions
2Measurement precision
If optical magnification correction is applied, then distortion errors are reduced, but other errors from low-frequency components and measurement conditions remain uncorrected
Solution Approach 1:
The patent changes the approach from correcting optical magnification errors to selecting high-frequency spatial components for measurement. By calculating the spatial frequency spectrum and selecting only the high-frequency range, the method makes measurement results insensitive to optical distortion, low-frequency surface variations, and lighting changes, thereby improving overall measurement reliability beyond what magnification correction alone can achieve
3Adaptability or versatility
If measurement is performed on surfaces with varying roughness, then versatility is improved, but measurement precision deteriorates due to low-frequency component interference
Solution Approach 1:
The patent extracts only the high-frequency spatial components from measurement target images by calculating the spatial frequency spectrum and selecting a specific frequency range. This extraction removes the harmful low-frequency components that vary with surface roughness, lighting conditions, and measurement distance, enabling consistent high-precision measurement across diverse surfaces including rough, smooth, shiny, and matte surfaces
Solution Approach 2:
The patent changes the measurement parameter from using the full spatial frequency spectrum to using only the high-frequency component range. This parameter change makes the measurement process adaptable to various surface conditions because high-frequency components represent local texture and edge information that remains consistent across different surface types, while filtering out low-frequency variations caused by surface roughness and lighting
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
The solution effectively reduces measurement errors by correcting for errors not related to optical magnification, specifically those caused by low-frequency components, resulting in improved precision and accuracy across varying surface roughness, distance, and speed conditions.
Implementation Method 1
obtains two image capturing signals by photoelectrically converting speckle distribution before and after motion
Implementation Method 2
calculate a measurement value with respect to a measurement target by using a cross-correlation function of two images of the measurement target
Data Source
AI summary
To provide a measurement apparatus and the like that suppresses an error caused by an image used for measurement, and that enables measurement with a high accuracy, in a measurement apparatus, a measurement unit is configured to calculate a measurement value with respect to a measurement target by using a cross-correlation function of two images of the measurement target acquired by an image capturing element, and a correction unit is configured to correct the measurement value according to a configuration of a spatial frequency component of the two images.