3D Scanner Error Correction Using Sector Calibration
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Solution Overview
Problem
3D range imaging cameras and other dimensioning devices face errors in distance measurement due to external interference, pixel saturation, and internal scattering, leading to reduced accuracy, necessitating a method for error correction.
Innovation Solution
A method involving the use of calibration objects with known dimensions to calculate and store measurement errors in sectors of the field of view, allowing for corrected measurements of target objects by applying these errors during scanning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If range imaging cameras are used for rapid 3D measurements, then measurement speed is improved, but measurement accuracy deteriorates due to external interference and internal scattering
Solution Approach 1:
The patent applies preliminary action by performing error characterization scans with calibration objects of known dimensions before actual measurement. The system pre-calculates and stores correction factors for each sector in the field of view, accounting for systematic errors from internal scattering and external interference. When measuring target objects, these pre-determined correction factors are applied to compensate for accuracy degradation while maintaining high measurement speed.
2Measurement precision
If laser scanning systems are used for 3D measurements, then measurement accuracy is improved, but measurement speed deteriorates due to point-by-point scanning
Solution Approach 1:
The patent applies segmentation by dividing the field of view into multiple sectors and characterizing errors independently for each sector using calibration objects. This allows the system to maintain the parallel processing capability of range imaging cameras while applying targeted corrections. Each sector's error profile is stored and applied independently, enabling accurate multi-point measurements without sacrificing the simultaneous detection advantage of array-based sensors.
3Area of stationary object
If multiple range imaging cameras are used simultaneously, then measurement coverage is improved, but measurement accuracy deteriorates due to cross-interference between cameras
Solution Approach 1:
The patent applies the intermediary principle by using calibration objects with known dimensions as mediators to characterize and quantify cross-interference effects between multiple cameras. These calibration objects serve as reference standards that allow the system to determine sector-specific error patterns caused by inter-camera interference. The measured errors are then stored as correction factors that can be applied to subsequent measurements, enabling accurate operation of multiple cameras simultaneously while maintaining expanded measurement coverage.
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 significantly improves the accuracy of 3D measurements by accounting for systemic errors, reducing measurement inaccuracies and ensuring results fall within acceptable tolerances.
Implementation Method 1
Each collector (e.g., pixel) of the image sensor simultaneously measures the time that it took for the light to travel from the illumination unit to the target object and back to the range imaging camera
Implementation Method 2
The reflected light is gathered by optics onto an image sensor
Data Source
AI summary
A method is presented for correcting errors in a 3D scanner. Measurement errors in the 3D scanner are determined by scanning each of a plurality of calibration objects in each of a plurality of sectors in the 3D scanner's field of view. The calibration objects have a known height, a known width, and a known length. The measurements taken by the 3D scanner are compared to the known dimensions to derive a measurement error for each dimension in each sector. An estimated measurement error is calculated based on scans of each of the plurality of calibration objects. When scanning target objects in a given sector, the estimated measurement error for that sector is used to correct measurements obtained by the 3D scanner.