Self-Leveling Pipe Inspection Imaging With Low-Memory Rotation
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Solution Overview
Problem
Existing self-leveling pipe inspection systems face challenges in maintaining real-time video feed due to high memory resource consumption, often requiring lossy processes like cropping or rescaling, which compromise image quality and field of view.
Innovation Solution
A self-leveling pipe inspection system that includes a camera head with an orientation sensing module, an image sensor, and an image processing module. The image processing module generates a second image corresponding to a subset of the first image's pixel values, selected based on an orientation signal, to provide an electronically level-adjusted image without significant memory resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional digital rotation using coordinate transformation and rotation matrices is applied, then image orientation is corrected, but memory resource consumption increases and video latency becomes unacceptable
Solution Approach 1:
The patent extracts only the essential orientation correction operation from the conventional rotation process. Instead of applying full coordinate transformation and rotation matrices to the entire image, the system identifies and processes only the necessary pixel repositioning based on orientation data, significantly reducing memory consumption while maintaining orientation accuracy.
Solution Approach 2:
The patent applies partial action by processing only the minimum necessary pixels for orientation correction rather than transforming the entire image coordinate system. This selective processing approach reduces computational load and memory requirements while achieving the required orientation correction for real-time video display.
2Productivity
If cropping or rescaling is applied to reduce memory consumption, then processing speed increases, but image quality and field of view are compromised
Solution Approach 1:
The patent changes the processing parameters by using orientation-based pixel selection instead of fixed cropping or rescaling ratios. This allows the system to maintain full image quality and field of view while achieving real-time processing speeds by dynamically adjusting which pixels need processing based on the actual orientation correction required.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves real-time video feed with improved image quality and field of view by selectively processing pixel values based on orientation signals, reducing memory consumption and latency.
Implementation Method 1
generating an orientation signal corresponding to an orientation of the image sensor, which may be a gravitation orientation
Data Source
AI summary
Self-leveling inspection system methods and devices for use in inspecting buried pipes or other cavities are disclosed. The system includes a camera head with an image sensor, an orientation sensor, and a signal processing module including a processing programmed to receive an image from the image sensor, and an orientation signal from the orientation sensor, generate a second image based at least in part on information provided from the orientation sensor, and store the second image in a non-transitory memory.