Multi-scale Surface Pattern for Stereo Distance Measurement
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Solution Overview
Problem
Existing distance measuring techniques using stereoscopy face challenges in accurately identifying points on homogeneous surfaces with color gradients, as existing patterns work optimally at one distance and struggle with varying distances due to increased pixel area representation.
Innovation Solution
A distance measuring element featuring a surface pattern composed of non-repeating sub-patterns on different scales, where the minimum distance between values of one range is greater than the maximum value of another range, allowing for improved distance measurement from near and far distances by ensuring distinctness across scales.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single-scale pattern is used for distance measurement, then the pattern can be clearly identified at one specific distance, but the pattern becomes difficult to distinguish at other distances due to pixel area variations
Solution Approach 1:
The surface pattern is segmented into multiple sub-patterns with different scales (first sub-pattern with smaller scale, second sub-pattern with larger scale). Each sub-pattern is optimized for specific distance ranges, allowing the system to clearly identify patterns at both near and far distances by selecting or combining appropriate sub-patterns.
Solution Approach 2:
The solution transitions from a single-scale pattern to a multi-scale pattern system, adding the dimension of scale variation. By creating sub-patterns with different spatial frequencies and sizes, the system can adapt to different viewing distances, effectively solving the problem of distance-range coverage while maintaining measurement precision.
2Area of stationary object
If pixels average more surface color values at greater distances, then larger areas are covered, but the distinctness of pattern values is reduced making identification difficult
Solution Approach 1:
Different sub-patterns are designed with locally optimized qualities suited for their intended distance ranges. The first sub-pattern uses smaller-scale variations suitable for near-distance identification, while the second sub-pattern uses larger-scale variations suitable for far-distance identification. This local optimization ensures that each sub-pattern maintains sufficient value distinctness for its target range despite pixel averaging effects.
3Quantity of substance
If homogeneous surfaces are measured using stereoscopy, then the surfaces can be viewed, but points cannot be identified due to identical color values across the surface
Solution Approach 1:
Instead of relying on the natural homogeneous color of surfaces, the invention applies artificial surface patterns with deliberate color or intensity variations. These patterns create distinguishable value differences across the surface, enabling point identification through stereoscopy even on previously homogeneous surfaces. The multi-scale sub-patterns ensure these variations remain detectable across different distances.
Data Source
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AI summary
The invention relates to a distance-measuring element (100) comprising: at least one first sub-pattern (30a) that has a non-repeating structure of values in a defined first value range (W1); and at least one second sub-pattern (30b) that has, with respect to the first sub-pattern (30a), a non-repeating structure of values in a second value range (W2), the second sub-pattern (30b) not having any values in the defined first value range (W1); the at least two sub-patterns (30a, 30b) being superposed in summary across a defined surface range to form a surface pattern (60); the minimum distance between the values of the second value range (W2) being greater than the maximum value of the first value range (W1).