3D Scanner Exposure Control Using Nonlinear Intensity Compression
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Solution Overview
Problem
Conventional 3D scanners face challenges in automatic exposure control when scanning larger volumes at greater distances and depths, leading to inaccurate measurements due to overexposure or underexposure of image data, particularly when using structured light stereovision.
Innovation Solution
Implementing a nonlinear image data compression method that amplifies low intensity signals while limiting saturation of high intensity signals, allowing for automatic exposure control based on compressed image data to maintain high resolution for low intensity values, enabling real-time scanning with portable scanners.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If conventional exposure control methods are used for scanning larger volumes at greater distances, then the scanning range and depth are improved, but the image data quality deteriorates due to overexposure or underexposure
Solution Approach 1:
The system performs preliminary actions by capturing a first image at a first exposure setting before final scanning, uses this preliminary image to determine optimal exposure parameters, then applies these parameters in subsequent scanning operations to prevent overexposure or underexposure across varying distances and volumes
Solution Approach 2:
The system implements feedback by analyzing the first captured image to determine background intensity values and reflectance characteristics, then using this feedback information to dynamically adjust exposure parameters for subsequent images, ensuring consistent image quality across different scanning distances and volumes
2Measurement precision
If manual exposure adjustments are made for different scanning distances, then the image data quality is improved, but the operation complexity and time consumption increase
Solution Approach 1:
The system performs self-service by automatically determining optimal exposure parameters through analysis of captured images and background intensity values, eliminating the need for manual exposure adjustments by operators while maintaining high image data quality across varying scanning conditions
Solution Approach 2:
The system automatically changes exposure parameters based on analyzed image data and background intensity values, dynamically adjusting exposure settings to suit different scanning distances and lighting conditions without requiring manual intervention
3Measurement precision
If high resolution is maintained for low intensity values through nonlinear compression, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The system applies local quality by using nonlinear compression specifically for low intensity values while handling high intensity values differently, preserving high resolution where it matters most (low intensity regions) without uniformly increasing complexity across the entire image processing pipeline
Data Source
AI summary
A scanning system for the 3D measurement of a surface of an object includes a 3D scanner and a computing system. The 3D scanner includes a scanner frame, a set of imaging modules and a communication module. The imaging modules include a light projector unit for projecting a structured light pattern onto the surface of the object, at least one camera for capturing image data, and at least one image data compression module that compresses the image data using a nonlinear conversion that compresses a dynamic range of intensity values in the compressed image data such that lower intensity values are amplified and mapped to a larger portion of the compressed dynamic range while amplification of higher intensity values is limited. The computing system controls an exposure setting of the 3D scanner based on background intensity values for images in the compressed image data. Related methods are also described.