Structured-Light Dimensioning with Dynamic Camera Settings
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Solution Overview
Problem
Structured-light dimensioning systems face challenges in capturing high-quality images of light patterns on all dimensioning surfaces, especially in handheld applications where lighting and object color variations hinder the imaging process, making it difficult to obtain resolvable patterns simultaneously.
Innovation Solution
A structured-light dimensioning system that includes a projector and camera subsystems with a control subsystem capable of capturing multiple pattern images using different camera settings, aligning them using the iterative closest point method to form an image composite with a resolvable light pattern on all surfaces, allowing for accurate dimension computation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single camera setting is used to capture the light pattern, then the imaging process is simple and fast, but the light pattern cannot be resolvable on all dimensioning surfaces under varying lighting and object color conditions
Solution Approach 1:
The system dynamically adjusts camera settings (exposure time, gain, white balance) based on the specific lighting and object color conditions detected for each dimensioning surface, allowing the camera to adapt to varying conditions rather than using a fixed setting
Solution Approach 2:
The system changes multiple camera parameters simultaneously (exposure time, gain, white balance) to optimize the capture of light patterns on surfaces with different reflectivity and color properties, ensuring resolvable patterns across all surfaces
2Reliability
If multiple camera settings are used to capture pattern images on all surfaces, then the light pattern becomes resolvable on all dimensioning surfaces, but the imaging process time increases
Solution Approach 1:
The system performs preliminary actions by capturing multiple pattern images with different camera settings in rapid succession before final processing, ensuring that at least one image will have resolvable patterns on all surfaces
Solution Approach 2:
The system merges multiple captured images into a single composite image that combines the resolvable light patterns from different camera settings, creating a complete and accurate representation of all dimensioning surfaces
3Ease of operation
If handheld operation is used for portability, then the system is mobile and adaptable, but motion variations cause misalignment and reduce measurement precision
Solution Approach 1:
The system uses feedback from feature detection and iterative closest point algorithm to detect and correct misalignment caused by hand motion, continuously adjusting the alignment based on measured features to maintain measurement precision
Solution Approach 2:
The system performs preliminary alignment using the iterative closest point algorithm to pre-correct for motion variations before final measurement computation, reducing the impact of hand motion on measurement accuracy
Data Source
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AI summary
A system and method for structured-light dimensioning is disclosed. The method includes combining multiple images using different camera settings to provide all of the information necessary dimensioning. What results is an improved ability to sense a light pattern reflected from an object's surfaces, especially when the lighting and/or object color make imaging all surfaces simultaneously difficult.