Machine Vision Position Measurement Using Image Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Machine vision inspection systems face challenges in achieving high accuracy for measuring distances between features that are separated by more than one field of view, as the accuracy of scale-based position encoders is not sufficient for certain applications.
Innovation Solution
The system operates in two states: a first state using scale-based position measurements and a second state using image correlation to provide enhanced position measurements, allowing for more accurate determination of image positions and distances between features by capturing overlapping images and applying image correlation techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scale-based position encoders are used to determine stage positions for measuring distances between features separated by more than one field of view, then the measurement process is simple and fast, but the measurement accuracy is insufficient
Solution Approach 1:
The measurement process is divided into two distinct operating states: a first state using scale-based position measurements for simple cases, and a second state using image correlation for enhanced accuracy. This segmentation allows the system to switch between methods based on the specific measurement needs, improving overall measurement precision without always incurring the complexity of image correlation.
Solution Approach 2:
The system dynamically switches between two operating states depending on the measurement requirements. The control system can transition from the first operating state (scale-based) to the second operating state (image correlation) when high precision is needed for features separated by more than one field of view, making the system adaptable to different measurement scenarios.
2Measurement precision
If image correlation is used to provide enhanced position measurements for features separated by multiple fields of view, then measurement accuracy is improved, but the process time and computational resources increase
Solution Approach 1:
The system applies image correlation selectively rather than universally. It uses the more time-consuming image correlation method only when needed (for features separated by more than one field of view requiring high precision), while using the faster scale-based method for other measurements, thus balancing accuracy requirements with measurement time.
Solution Approach 2:
The control system dynamically selects between operating states based on the specific measurement task. When features are within a single field of view or when high precision is not critical, the system uses the faster first state. When features are separated by multiple fields of view and high precision is required, it transitions to the second state with image correlation, optimizing the trade-off between time and accuracy.
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 enhances measurement accuracy for distances between features separated by multiple fields of view, reducing errors and improving precision beyond what is achievable with traditional scale-based measurement techniques.
Implementation Method 1
an imaging system that images the workpiece
Implementation Method 2
an imaging system that images the workpiece
Implementation Method 3
a scale-based measurement portion that provides position measurements indicative of the stage position relative to the imaging system
Implementation Method 4
providing the position of at least one second-state image based on enhanced second-state position measurement provided by using image correlation
Data Source
AI summary
A method utilizing image correlation to determine position measurements in a machine vision system. In a first operating state, the machine vision system utilizes traditional scale-based techniques to determine position measurements, while in a second operating state, image correlation displacement sensing techniques are utilized to determine position measurements. The image correlation techniques provide for higher accuracy for measuring distances between features that are separated by more than one field of view. The user may toggle between the operating states through a selection on the user interface, and guidance may be provided regarding when the image correlation mode is likely to provide higher accuracy, depending on factors such as the distance to be measured and the characteristics of the surface being measured.