Laser Scan Marker Detection Using Local Super-Resolution
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Solution Overview
Problem
Existing methods for detecting scan reference markers in scan data require high-resolution images or intensity data, which can be costly and time-consuming, and are influenced by factors like lighting conditions, limiting the maximum detectable range and increasing scanning costs.
Innovation Solution
A method involving a first marker detection algorithm followed by a resolution enhancement algorithm, such as super-resolution, to enhance the resolution of scan data sections, allowing for improved detection of scan reference markers, even at lower initial scanning resolutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution scanning is used to improve detection accuracy, then measurement precision is improved, but scanning time and cost increase
Solution Approach 1:
The scanning area is divided into multiple regions, and only the regions containing reference markers are scanned at high resolution. The rest of the area is scanned at lower resolution, thereby reducing overall scanning time while maintaining detection accuracy where needed.
Solution Approach 2:
Different scanning resolutions are applied to different regions of the scan data. High resolution is applied locally to areas with reference markers for accurate detection, while lower resolution is used for areas without markers, optimizing the balance between accuracy and scanning speed.
2Reliability
If high-resolution images are used for marker detection, then detection reliability is improved, but lighting conditions have greater influence on detection accuracy
Solution Approach 1:
Instead of relying on reflected light intensity which is affected by lighting conditions, the system uses the known geometric pattern of reference markers as a template and compares it with the scanned regions. This pattern matching approach creates a copy-based detection method that is invariant to lighting changes.
Solution Approach 2:
The reference markers use high-contrast patterns (such as black and white alternating quadrants) that create strong geometric signatures. These pattern-based identifiers remain detectable regardless of lighting conditions because the detection relies on geometric shape recognition rather than intensity measurement.
3Device complexity
If conventional template matching algorithms are used, then device complexity is reduced, but detection accuracy decreases at long distances
Solution Approach 1:
The system performs preliminary actions by scanning the entire area at a first resolution to identify potential marker locations, then applies a resolution enhancement algorithm specifically to those identified regions before performing template matching. This preliminary scanning at lower resolution reduces the computational burden of subsequent high-precision detection.
Solution Approach 2:
A resolution enhancement algorithm acts as an intermediary between the low-resolution scan data and the template matching process. This intermediary algorithm upsamples the identified marker regions to high resolution, enabling accurate template matching without requiring the entire scan to be performed at high resolution initially.
Data Source
AI summary
A computer-implemented method for the detection of scan reference markers within scan data provided by a laser scanner, wherein the scan reference markers are to be fixedly positioned within a scene and provide for a fixed absolute position reference in said scene. Therefore, the computer-implemented method comprises multiple steps. Firstly, the scan data is provided as a three-dimensional visual representation of a scene. Secondly, a first marker detection algorithm is applied to the scan data configured to identify scan reference marker candidates, wherein for each of the identified scan reference marker candidates a section in the scan data is defined. Further, a resolution enhancement algorithm may be applied to the defined section in the scan data, wherein the resolution enhancement algorithm is configured to obtain a comparably higher resolution of the defined section and provide a high-resolution section of the scan reference marker candidate.