Camera Alignment in Pipe Networks Using Image Processing
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Solution Overview
Problem
Existing camera alignment methods for sewer pipe inspection are prone to positioning errors due to dirt, wear, and geometric variations in pipes, leading to inaccurate imaging and perspective distortions, especially when capturing distant sections.
Innovation Solution
A method that determines the pipeline geometry from camera images and aligns the camera's optical axis with the pipe axis using image processing and actuators, allowing for precise positioning and zooming without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the camera is positioned manually based on predetermined parameters, then the setup process is simple, but positioning accuracy deteriorates due to dirt, wear, and geometric variations
Solution Approach 1:
The camera system performs self-alignment by automatically detecting geometric features in the pipeline images and computing its own optimal position and orientation. The evaluation unit processes images to determine the pipeline geometry and calculates the necessary camera adjustments, eliminating the need for manual positioning based on potentially inaccurate predetermined parameters.
Solution Approach 2:
The system uses feedback from image analysis to correct positioning errors. By continuously evaluating images of the pipeline and comparing the detected geometry with the actual camera position, the system computes correction values that are fed back to adjust the camera orientation, compensating for errors caused by dirt, wear, and geometric variations.
2Ease of operation
If the camera is skewed relative to the pipeline, then the system remains simple to operate, but imaging quality deteriorates with perspective distortions and incomplete coverage
Solution Approach 1:
The patent replaces manual mechanical alignment procedures with an automated image-processing-based alignment system. Instead of relying on physical positioning skills and predetermined parameters, the system uses computational algorithms to analyze images and automatically calculate the optimal camera orientation, substituting mechanical adjustment with digital processing.
Solution Approach 2:
The camera positioning system transitions from a static predetermined position to a dynamic adjustment mechanism. The system continuously evaluates images and automatically adjusts camera orientation in real-time, allowing the camera to adapt its position based on the actual pipeline geometry rather than relying on fixed, potentially inaccurate predetermined parameters.
3Measurement precision
If automated alignment is implemented, then positioning accuracy is improved, but device complexity increases
Solution Approach 1:
The evaluation unit serves multiple functions: it processes images, detects geometric features, determines pipeline geometry, calculates camera position errors, and computes correction values. By consolidating these functions into a single multi-functional unit, the system achieves automated alignment without proportionally increasing overall system complexity.
Solution Approach 2:
The patent introduces an intermediary evaluation unit that acts as a mediator between the camera and the control system. This intermediary processes images and computes the necessary alignment corrections, separating the complex image processing tasks from the control mechanisms and allowing for modular, manageable system architecture.
Data Source
AI summary
A method for aligning a camera in a pipe network comprising a pipeline, characterized by the steps: a. Inserting the camera into the pipe network, b. Recording at least one image representing a view of the pipeline, c. Determining the geometry of the pipeline based on the at least one image, and d. Aligning the camera such that the optical axis of the camera lies in the axis of the pipeline.