3D Measurement Intersection Interval Error Reduction
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Solution Overview
Problem
Conventional three-dimensional measurement techniques using spatial coding face errors in intersection point and interval calculations due to sampling errors from straight-line approximation and luminance shifts, especially when using a small number of image sensor pixels or under high ambient light conditions, leading to inaccuracies in object shape measurement.
Innovation Solution
A three-dimensional measurement apparatus and method that detects intersection positions between pattern lights using tone values from captured images and calculates a third position based on adjacent intersection positions to determine accurate intersection intervals, reducing errors and improving measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional straight-line approximation method is used to detect intersection points, then the detection process is simple, but sampling errors occur leading to inaccurate intersection intervals
Solution Approach 1:
The patent segments the intersection point detection process into multiple stages: first detecting candidate intersection points using straight-line approximation, then refining these points by analyzing tone value relationships between first and second pattern lights. This segmentation allows the system to maintain computational simplicity while improving accuracy through multi-step processing.
Solution Approach 2:
The patent performs preliminary detection of intersection points using the simple straight-line approximation method, then uses these preliminary results as the basis for more accurate refinement. The preliminary action of detecting candidate points enables subsequent precision improvement without starting from scratch.
2Device complexity
If one period of pattern light is sampled with a small number of image sensor pixels, then the apparatus size and cost are reduced, but sampling errors increase leading to inaccurate measurements
Solution Approach 1:
The patent changes the parameter of intersection point calculation from direct pixel-based straight-line approximation to a method based on tone value relationships. By calculating intersection points from the relationship between tone values of first and second pattern lights rather than direct pixel sampling, the system achieves higher accuracy with fewer pixels.
Solution Approach 2:
The patent replaces the mechanical sampling approach (relying on high-resolution image sensors to capture sufficient data points) with a computational approach (using tone value relationships and mathematical calculations to determine intersection points). This substitution allows accurate measurement without requiring high pixel counts.
3Measurement precision
If high-resolution image sensor is used to reduce sampling errors, then measurement accuracy improves, but apparatus size and cost increase
Solution Approach 1:
The patent fundamentally changes the parameter used for intersection point detection from spatial sampling density (pixel count) to tone value relationships. By using the relationship between tone values of first and second pattern lights, the system achieves high measurement accuracy without requiring high spatial sampling density, thus avoiding the need for expensive high-resolution sensors.
4Ease of operation
If ambient light causes high luminance values in captured images, then the imaging process remains simple, but intersection point detection accuracy deteriorates
Solution Approach 1:
The patent converts the harmful effect of ambient light into a useful signal by utilizing the differential relationship between tone values. Instead of being disrupted by ambient light affecting absolute luminance values, the system uses the relationship between tone values of first and second pattern lights, where ambient light effects cancel out, transforming the harmful ambient light into a non-interfering condition.
Solution Approach 2:
The patent introduces tone value relationships as an intermediary between the captured images and intersection point detection. Rather than directly detecting intersection points from raw image data (which is sensitive to ambient light), the system uses tone value relationships as an intermediate step that is insensitive to ambient light, thereby protecting the measurement accuracy.
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
The method significantly reduces errors in intersection intervals, enabling more accurate three-dimensional measurements, even with a small number of image sensor pixels and under high luminance conditions, by calculating intersection intervals from third positions, thus improving the precision of object shape determination.
Implementation Method 1
an image capturing apparatus captures the target object onto which the spatial code is projected
Data Source
AI summary
A three-dimensional measurement apparatus comprises a detection unit configured to detect a plurality of intersection positions between first pattern light in which a bright part and a dark part are alternately arranged and second pattern light in which a phase of the first pattern light is shifted, by using tone values of a first image obtained by capturing a target object onto which the first pattern light is projected and tone values of a second image obtained by capturing the target object onto which the second pattern light is projected; and a measurement unit configured to calculate a third position based on a first intersection position included in the plurality of intersection positions and a second intersection position that is adjacent to the first intersection position and measure a three-dimensional position of the target object based on an interval between the third positions.