Lane Line Detection Using Front Rear Camera Matching
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Solution Overview
Problem
Existing lane departure warning systems, especially those used in dashcams, face challenges in accurate lane line detection due to image distortion from wide-angle lenses, low frame rates, and varying environmental conditions, leading to increased false alerts and missed detections.
Innovation Solution
A method and system for lane line detection in vehicles equipped with front and rear camera modules, which collect historical speed trajectories and image frames, match images between cameras, and analyze lane line features using probabilistic calculations to improve detection accuracy without requiring complex AI algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple image recognition techniques or reduced-complexity neural network models are used in dashcams, then the device complexity and computational requirements are reduced, but the image recognition accuracy decreases leading to increased false alerts and missed detections
Solution Approach 1:
The patent combines front camera and rear camera images to perform lane line detection. By merging information from multiple camera views and integrating historical detection results with current frame analysis, the system achieves higher recognition accuracy without requiring complex AI algorithms in each individual camera module.
Solution Approach 2:
The system performs preliminary image processing and feature extraction before final lane line detection. Historical detection results are collected and stored in advance, and current frames are pre-processed to identify potential lane line features before applying the detection algorithm, which improves accuracy while keeping computational complexity manageable.
2Area of stationary object
If wide-angle lenses are used in dashcams, then the field of view is increased, but image distortion occurs at the edges reducing detection accuracy
Solution Approach 1:
The patent introduces an image matching and coordinate transformation process as an intermediary between image capture and lane line detection. The system matches features between front and rear camera images, performs coordinate transformations to correct for distortion, and uses these corrected coordinates for accurate lane line detection despite the wide-angle distortion.
3Productivity
If low frame rates are used in dashcams, then the processing load is reduced, but the ability to detect lane lines under varying environmental conditions deteriorates
Solution Approach 1:
The system continuously accumulates historical detection results and maintains a running record of lane line positions across multiple frames. Even at low frame rates, this continuous accumulation of detection data allows the system to track lane lines reliably through varying environmental conditions by comparing current detections with historical trends.
Data Source
AI summary
A method is provided for a travelling vehicle to detect lane lines. A front camera module captures frames of front image of the vehicle, a rear camera module captures frames of rear image of the vehicle, and a speed sensor module senses speed trajectory of the vehicle. In the method, the frames of front image, the frames of rear image and the sensed speed trajectory are used to obtain pairs of matched front and rear images, and to determine reliability of a lane line feature detected in a current front image or a current rear image based on the pairs of matched front and rear images, and the lane line feature detected from the current front image or the current rear image is outputted upon determining that the currently detected lane line feature is reliable.