Video Camera Image Stabilization via Lane Reference Correction
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Solution Overview
Problem
Existing image stabilization methods for video cameras in road traffic monitoring fail to effectively compensate for vibrations and deformations caused by temperature gradients and wind, leading to inaccurate image processing and increased false alarms, as they assume stationary cameras, which is not the case when cameras are mounted on deforming poles.
Innovation Solution
A method that determines stable image portions corresponding to preferred lanes, uses differential processing to identify complementary portions, and adjusts image vectors to restore a stationary reference point, ensuring image stability by processing images to counteract camera movements relative to a three-dimensional frame of reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If mechanical stabilization systems are integrated in the camera to cancel vibration effects, then image stability is improved, but device cost and complexity increase significantly
Solution Approach 1:
The patent replaces mechanical stabilization systems with an optical/image processing approach. The method uses image processing algorithms to detect and compensate for camera movements by analyzing sequential frames and calculating displacement vectors, thereby achieving stabilization without mechanical components.
Solution Approach 2:
The patent introduces an intermediary image processing system that acts as a mediator between the unstable camera output and the final stabilized image. This intermediary layer processes the image data to correct for vibrations caused by pole deformations.
2Stability of the object's composition
If complex image processing algorithms are used to stabilize images, then image stability is improved, but hardware costs and processing requirements increase
Solution Approach 1:
The patent segments the image processing task into distinct stages: detecting stationary objects, calculating displacement vectors, and applying corrections. This segmentation allows for more efficient processing and reduces overall system complexity.
Solution Approach 2:
The patent performs preliminary detection of stationary objects and calculation of displacement vectors before applying the actual stabilization correction. This preliminary action prepares the data in advance, making the final correction more efficient and reducing processing requirements.
3Device complexity
If image stabilization is not performed, then hardware costs are reduced, but measurement precision and incident detection accuracy deteriorate
Solution Approach 1:
The patent enables the image processing system to self-correct for vibrations by using the image data itself to detect and compensate for camera movements. The system uses stationary objects in the scene as reference points to calculate and correct displacements, making the stabilization process self-sufficient.
4Ease of manufacture
If cameras are mounted on existing poles for traffic monitoring, then installation cost is reduced, but image stability deteriorates due to pole vibrations and deformations
Solution Approach 1:
The patent converts the harmful effect of pole vibrations into a detectable signal that can be measured and corrected. By using the vibration-induced displacement of stationary objects as a reference, the system can calculate and compensate for the vibrations, turning a disadvantage into a useful measurement basis.
Data Source
AI summary
Method and device for stabilizing images obtained by a video camera of an environment with objects moving along lanes. The method a first stage of determining in first images obtained by the camera, portions corresponding to the movement lanes, determining the remaining second portions complementary to the first portions, determining, in the second portions, the reference position of the image point corresponding to a first stationary object point, and a second stage of determining in at least one second image taken after the first images, the vector that corresponds to the movement of the image point relative to its reference position determined by the first images, and processing the second image as a function of the modulus and direction of the vector such that, relative to the three-dimensional frame of reference the image point returns to its reference position.