Automatic Maximal Clamp Measurement Tool for Machine Vision
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Solution Overview
Problem
Existing machine vision tools for measuring distances are limited by their 1D nature, leading to accuracy issues, sensitivity to alignment, noise filtering problems, lack of flexibility in edge polarity detection, and inability to reject invalid configurations, particularly when dealing with complex 2D shapes.
Innovation Solution
A machine vision based automatic maximal clamp measurement tool that detects curves or edges in a specified region of interest, analyzes and validates them based on user-defined constraints, applies calibration to correct for distortions, and determines valid clamp points to measure distances accurately, even in complex geometries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If edge probe based caliper tools are used to measure distance between edge points, then measurement can be performed on 2D images, but measurement accuracy deteriorates due to 1D nature and alignment sensitivity
Solution Approach 1:
The patent transitions from 1D edge probing to 2D curve analysis by detecting complete contours and using convex hull algorithms. This dimensional expansion allows the system to analyze shapes in their full 2D complexity, eliminating alignment sensitivity and improving measurement precision while maintaining ease of operation through automated curve detection.
Solution Approach 2:
The patent replaces the mechanical caliper approach with computational geometry methods. Instead of physically probing edges, the system uses image processing to detect curves, compute convex hulls, and calculate distances algorithmically, achieving higher precision without mechanical alignment requirements.
2Adaptability or versatility
If multiple edge probe based clamp tools are used to measure maximum distance, then measurement coverage is extended, but accuracy deteriorates due to gaps between discrete edge points
Solution Approach 1:
The patent employs continuous curve detection algorithms that trace complete contours without discrete gaps. By using curve fitting and convex hull computation, the system maintains continuous analysis of the entire object boundary, eliminating the gaps present in discrete edge probing and ensuring accurate measurement of maximum dimensions.
Solution Approach 2:
The system moves from discrete 1D edge points to continuous 2D curve representations. This dimensional transition enables comprehensive coverage of the object's maximum dimensions while maintaining measurement precision through continuous geometric analysis rather than sampling at discrete intervals.
3Adaptability or versatility
If multiple edge probe based clamp tools are used, then measurement direction flexibility is improved, but sensitivity to alignment increases causing inaccurate measurements when misaligned
Solution Approach 1:
The patent computes the convex hull of detected curves, creating a minimal enclosing polygon that inherently aligns with the object's maximum dimensions. This approach eliminates alignment sensitivity because the convex hull automatically adapts to the object's geometry, providing accurate measurements regardless of the original image orientation or probe alignment.
Solution Approach 2:
The system performs self-alignment through convex hull computation, where the algorithm automatically identifies the optimal measurement framework based on the detected curves. This self-service alignment mechanism eliminates the need for manual calibration or precise pre-alignment, maintaining measurement precision across all orientations.
4Productivity
If edge probe based tools are used, then measurement speed is maintained, but noise filtering capability deteriorates due to inability to distinguish noisy edges from valid features
Solution Approach 1:
The patent uses continuous curve detection and convex hull computation that naturally filters noise through mathematical operations. The convex hull algorithm inherently ignores isolated noisy points by computing the minimal enclosing shape based on the overall curve distribution, maintaining both speed and reliability through efficient geometric processing.
Solution Approach 2:
The system replaces edge detection with computational geometry methods. Instead of relying on potentially noisy edge probes, the patent uses curve fitting, convex hull algorithms, and geometric analysis to identify valid features, providing robust noise filtering while maintaining measurement speed through efficient mathematical operations.
5Device complexity
If simple edge detection is used, then device complexity is reduced, but ability to analyze 2D shape deteriorates leading to inability to reject invalid configurations
Solution Approach 1:
The patent extends simple edge detection to 2D curve analysis and convex hull computation. This dimensional expansion enables the system to analyze the full 2D geometry of objects, identify valid configurations through geometric relationships, and reject invalid measurements while maintaining reasonable computational complexity through efficient algorithms.
Solution Approach 2:
The system performs preliminary curve detection and convex hull computation to establish a geometric framework before validation. This preliminary analysis prepares the data structure needed for subsequent validity checks, enabling reliable configuration rejection without requiring complex real-time validation algorithms.
Data Source
AI summary
System and method for measuring distances in an image. An image is received that includes curves corresponding to one or more objects in the image. Multiple curves in a specified region of interest (ROI) in the image are detected, where the ROI has a specified direction. Each curve includes respective curve points. A convex hull is determined based on the respective curve points. One or more candidate antipodal point pairs of the convex hull are determined. A first point pair of the one or more antipodal point pairs is selected based on one or more specified constraints. A clamp angle corresponding to the first point pair is determined. A distance between the first point pair along a direction specified by the clamp angle is determined. The first point pair, the distance, and the clamp angle are stored. Calibration information may be applied at any point during the process.