Automated Camera Calibration Control Point Detection

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Solution Overview

Problem

Manual identification of control points in camera calibration patterns is inefficient and prone to errors due to lens distortion and orientation issues, requiring human assistance.

Innovation Solution

A camera calibration device applies filters to images of calibration patterns to determine control points by distinguishing between interior and boundary points using derivatives, allowing for automated and accurate calibration without human intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual identification of control points is used, then human assistance can provide flexibility, but the process becomes inefficient and error-prone

Engineering Contradiction:

Improveaccuracy of control point identificationVSAvoidefficiency of calibration process

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs automated detection of control points using image processing algorithms, eliminating the need for manual human intervention. The calibration device automatically identifies and selects control points from calibration patterns, making the system self-sufficient and improving both efficiency and consistency.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical identification processes with automated computational algorithms. Image processing techniques automatically detect control points based on pattern recognition and geometric constraints, substituting human visual inspection and selection with digital processing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated detection is implemented, then efficiency improves, but complexity of the calibration device increases

Engineering Contradiction:

Improveefficiency of control point determinationVSAvoidcomplexity of calibration system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The calibration process is divided into distinct stages: image acquisition, feature detection, control point identification, and calibration computation. Each stage uses specialized algorithms optimized for its specific task, making the overall complex process manageable through modular segmentation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system adjusts detection parameters and algorithmic approaches based on the specific calibration pattern and imaging conditions. By optimizing parameters such as threshold values, detection sensitivity, and geometric constraints, the system achieves robust automated detection without requiring excessive computational complexity.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS9319666B1Detecting control points for camera calibration

Publication Date: 2016.04.19 MATHWORKS INC

AI summary

A device is configured to receive an image including a calibration pattern and apply a filter to the image based on a first coordinate plane. The device is configured to determine a first set of response peaks associated with the calibration pattern based on applying the filter, the first set of response peaks being associated with a set of control points and a set of boundary points. The device is configured to determine a second set of response peaks associated with the calibration pattern based on a second coordinate plane and a third coordinate plane, the second set of response peaks being associated with the boundary points. The device is configured to determine the control points based on determining the first set of response peaks and the second set of response peaks, and provide information that identifies the control points.