Vehicle Camera Image Correction via Road Feature Tracking
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Solution Overview
Problem
Existing image correction methods for imaging devices in vehicles are limited by the need for special conditions like patterned ground for initial calibration, and require re-calibration when the device's position changes due to external factors, which can be burdensome and time-consuming.
Innovation Solution
An image correction method and system that collects images from a vehicle-mounted imaging device, determines feature points, detects corresponding points, calculates movement information, and derives a correction parameter using homography to correct image offsets while the vehicle is in motion, allowing for continuous image correction without time or space constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image correction is performed using traditional methods with patterned ground, then correction accuracy is improved, but the process requires special conditions and driver mobility
Solution Approach 1:
The system uses the imaging device itself to capture images of the road surface and extract feature points, eliminating the need for external patterned grounds or driver mobility. The correction process serves itself by using the device's own imaging capability to perform calibration
Solution Approach 2:
The road surface is transformed into a universal calibration target that can be used anywhere the vehicle travels. Instead of requiring special patterned grounds, any road surface with detectable features (cracks, patterns, markings) can serve as the correction reference, making the system universally applicable
2Measurement precision
If image correction is performed after imaging device position changes, then correction accuracy is restored, but time and space constraints are imposed
Solution Approach 1:
The system enables continuous image correction by processing images captured during normal vehicle operation. Instead of requiring periodic stops for recalibration, the correction can be performed continuously as the vehicle travels, eliminating time loss and maintaining constant image quality
Solution Approach 2:
The correction system transitions from static calibration (requiring vehicle stops at specific locations) to dynamic calibration (performing correction during vehicle motion). The system adapts to changing imaging device positions in real-time by continuously capturing and processing images during movement
3Measurement precision
If image correction requires special location conditions, then correction precision is ensured, but system adaptability is reduced
Solution Approach 1:
The road surface serves as a universal calibration target that functions in any location the vehicle travels. The system can extract feature points from various road surfaces (cracks, patterns, markings, lane dividers), making the correction process adaptable to any geographic location without sacrificing precision
Solution Approach 2:
The system changes the calibration reference from fixed patterned grounds to variable road surface features. By detecting and adapting to different feature types (cracks, patterns, markings, lane dividers) on various road surfaces, the system maintains correction precision across diverse locations and conditions
Data Source
AI summary
An image correction method and system. The image correction method includes collecting a plurality of images captured at different time points by an imaging device installed in a vehicle, determining a plurality of feature points in a first image captured at a first time point among the plurality of images, detecting corresponding points respectively matching the plurality of feature points in a second image captured at a second time point following the first time point among the plurality of images, determining movement information of the plurality of feature points based on the plurality of feature points and a result of detecting, determining a correction parameter based on the movement information, and performing image correction based on the correction parameter.