Structured Light 3D Camera Dynamic Exposure Control
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Solution Overview
Problem
Structured light based 3D cameras face challenges in accurately determining optimal exposure levels due to varying environmental factors, such as object reflectivity and illumination conditions, which affects pattern discrimination and 3D data precision.
Innovation Solution
A method and system that automatically determine an optimal exposure level by analyzing captured images, generating characteristic curves for pixel intensity variations, calculating intensity differences, and adjusting exposure to maximize pattern discrimination across different environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the camera iris is controlled to receive more light for objects with low reflectivity, then the pattern capture ability improves, but the exposure level becomes unsuitable for objects with high reflectivity causing saturation
Solution Approach 1:
The patent implements dynamic exposure control by automatically adjusting the camera exposure level based on real-time analysis of the captured image characteristics. The system calculates the standard deviation of pixel intensities and uses this metric to adaptively set the optimal exposure level, enabling the camera to dynamically adapt to varying object reflectivity properties during the scanning process
Solution Approach 2:
The system employs feedback mechanisms by analyzing the captured image data and using the calculated standard deviation as a feedback signal to adjust the exposure level. This closed-loop control ensures that the exposure is optimized based on the actual lighting conditions and object properties observed in the captured patterns
2Reliability
If the camera iris is controlled to receive limited light to prevent saturation for high reflectivity objects, then saturation is reduced, but the pattern capture ability deteriorates for low reflectivity objects
Solution Approach 1:
The system dynamically adjusts exposure levels during the structured light scanning process. By calculating the standard deviation of pixel intensities from captured patterns, the system determines whether to increase or decrease exposure, enabling it to prevent saturation for high reflectivity objects while maintaining adequate exposure for low reflectivity objects
Solution Approach 2:
The patent changes the exposure parameter adaptively based on the statistical properties of the captured image data. By monitoring the standard deviation of pixel intensities and adjusting the exposure level accordingly, the system optimizes the balance between preventing saturation and maintaining pattern visibility across different object reflectivity conditions
3Ease of operation
If fixed exposure level is used, then the system operation is simple, but the pattern discrimination accuracy deteriorates under varying environmental conditions
Solution Approach 1:
The system performs self-adjustment of the exposure level by automatically analyzing the captured image characteristics and determining the optimal exposure setting. The camera system serves itself by using its own captured data to guide exposure adjustments, eliminating the need for manual intervention while maintaining high pattern discrimination accuracy under varying environmental conditions
4Measurement precision
If exposure level is adjusted for each object type, then pattern discrimination accuracy improves, but the system complexity increases due to need for object classification
Solution Approach 1:
Instead of implementing complex object classification systems, the patent directly adjusts the exposure parameter based on the statistical properties (standard deviation) of the captured image data. This approach achieves object-adaptive exposure control through simple parameter changes based on real-time image analysis, avoiding the need for complex classification algorithms
Data Source
AI summary
Provided are a method and system for determining an optimal exposure of a structured light based 3D camera. The system includes a projecting means for illuminating a predetermined pattern on a target object, an image capturing means for capturing an image of the target object with the pattern projected, and a processing means for reconstructing 3D data for the target object by identifying the pattern of the captured images from the image capturing means. The system automatically determines an optimal exposure of the structured light based 3D camera system through analyzing the captured image of the target object.