Calibration Pattern Point Identification via Template Deviation
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Solution Overview
Problem
Existing methods for identifying characteristic points in calibration patterns within images often yield false positives due to noise or background interference, requiring high computing capacity to distinguish true points from secondary points.
Innovation Solution
A method involving overlaying a template arrangement of template points over candidate points, calculating the degree of deviation by summing distances between template points and their closest candidates, and using a threshold to identify true characteristic points, which is computationally simple and efficient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional filtering and thresholding methods are used to identify characteristic points, then the identification process can be performed, but false positive points are generated due to noise and background interference
Solution Approach 1:
The patent introduces an intermediary verification step between candidate point detection and final identification. A template matching mechanism acts as a mediator that compares each candidate point against a reference calibration pattern template, filtering out false positives while confirming true characteristic points through template correspondence validation
Solution Approach 2:
The patent implements feedback by using the known calibration pattern structure to verify candidate points. The system compares detected candidate points against the expected geometric relationships in the calibration pattern, providing feedback that confirms or rejects each candidate point based on whether it符合 the known pattern structure
2Measurement precision
If complex algorithms are used to distinguish true characteristic points from false positives, then identification accuracy improves, but computing capacity requirements increase
Solution Approach 1:
The patent performs preliminary action by pre-defining the calibration pattern template and its characteristic geometric relationships before the actual point identification process. This pre-processing creates a reference framework that simplifies the subsequent verification step, avoiding the need for complex real-time analysis
Solution Approach 2:
The patent uses a simple yet effective template matching approach that requires minimal computational resources. Instead of employing complex machine learning models or sophisticated algorithms, the system uses straightforward geometric comparison against a pre-defined template, achieving high precision with low computational cost
Data Source
AI summary
A method for identification of characteristic points of a calibration pattern within an image includes: (i) overlaying a template arrangement of template points over the candidate point such that a principal point of the template points coincides with the candidate point, wherein the template arrangement corresponds to the calibration pattern or to a sub-pattern of the calibration pattern, (ii) for each template point of the template arrangement, except the principal point, identifying from the set of candidate points the candidate point closest to the template point, and (iii) determining a degree of deviation by summing the distances between each template point of the template arrangement, except the principal point, and the candidate point closest to this template point; and identifying as characteristic points of the calibration pattern all those candidate points of the set of candidate points with a degree of deviation below a deviation threshold.