Single Camera Optical Measurement Using Segmented Target
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Solution Overview
Problem
Optical measurement systems using a single camera face significant accuracy disparities when estimating distance due to errors proportional to the square of the measured distance and inversely proportional to the object's size, particularly in determining distance and height differences.
Innovation Solution
An optical measurement system employing a specially configured target object with contrasting markings and a single camera, utilizing image processing techniques like SURF and mathematical optimization to improve accuracy, including the use of an inclination sensor for unlevelled environments, and multiple cameras for unlevelled target objects to estimate distance, height differences, and position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single camera is used for optical measurements, then device complexity is reduced, but measurement precision deteriorates due to errors proportional to the square of the distance and inversely proportional to the object size
Solution Approach 1:
The target object is segmented into multiple contrasting markings (e.g., 5-20 markings) with known geometric characteristics distributed along its length. This segmentation allows the system to measure distances to multiple reference points on the target, improving overall measurement precision while using a single camera.
Solution Approach 2:
The patent introduces a specially configured target object with contrasting markings as an intermediary element. This target serves as a mediator between the single camera and the measurement process, providing known geometric references that enable accurate distance and orientation calculations without requiring multiple cameras.
2Measurement precision
If the object size is increased to improve measurement accuracy, then measurement precision improves, but the applicability to real-world objects of varying sizes deteriorates
Solution Approach 1:
The target object incorporates localized contrasting markings at specific positions along its length, with each marking having known geometric characteristics. This local quality approach allows the system to use the entire target object for measurements while maintaining reference accuracy through the strategically placed markings, making the system adaptable to various real-world object sizes.
Solution Approach 2:
The patent employs mathematical optimization procedures that adjust measurement parameters based on the detected positions of contrasting markings. By changing the measurement approach from direct pixel-based measurement to optimization-based calculation using known geometric parameters of the markings, the system achieves high accuracy regardless of the target object's physical size.
3Measurement precision
If image processing complexity is increased to achieve subpixel accuracy, then measurement precision improves, but processing time and computational resources increase
Solution Approach 1:
The target object is pre-configured with contrasting markings that have known geometric characteristics and relationships. This preliminary preparation of the target object with embedded measurement references allows the image processing to focus on detecting and locating these pre-defined features, significantly reducing the computational complexity compared to analyzing arbitrary objects.
Solution Approach 2:
The patent replaces complex mechanical measurement systems with optical-mathematical processing. Instead of using multiple cameras or complex mechanical positioning systems, the solution substitutes a single camera combined with mathematical optimization procedures (such as least squares adjustment) to achieve subpixel accuracy, reducing processing time while maintaining precision.
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
Significantly enhances the accuracy of optical measurements for distance, height differences, and position determination, achieving subpixel accuracy and robustness in various environmental conditions, including unlevelled setups.
Implementation Method 1
an optical image is used for measuring angles between a camera position and two (2) objects on the image
Implementation Method 2
all (or substantially all) of the contrasting boundaries/edges on the target object are located and identified on the image by applying certain image processing such as SURF (Speeded Up Robust Features)
Implementation Method 3
the size of the target object on the image is estimated by applying certain mathematical optimization procedures such as least square regression using the identified locations of the contrasting boundaries/edges
Implementation Method 4
The image is then processed to remove optical distortions (e.g., using the well-known Brown-Conrady image distortion model)
Data Source
AI summary
An optical measurement system and method that utilizes a single camera in combination with a specially configured target object which significantly improves optical measuring accuracy with respect to the measurement of distance, height difference and position.